Input: The UNHCR supported in engaging refugee communities and leaders. The RRS facilitated access to all camps for the survey teams; this is the first time that the RRS facilitated access to all camps for such an extensive survey. Notably, the UNHCR and RRS facilitated the collaboration of the field workers with refugee leaders in each camp and Addis Ababa to support the teams in identifying sampled households and maintaining the safety of the field workers, and the sampled households during the entire survey period. The World Bank team led the collaboration between ESS, UNHCR, and RRS and provided technical support to the ESS since the project’s inception. The SESRE used a logistics plan similar to HoWStat. Six ESS branches were responsible for administering the survey: the Asayita, Gondar, Jigjiga, Negele, Gambella, Assosa, and Addis Ababa branches. Twenty-four field teams carried out the fieldwork, each consisting of one statistician, one team supervisor, and four enumerators. All field staff involved in the SERSE participated in the HoWStat survey. Enumerators were knowledgeable about local cultures and languages and could detect inconsistencies and misunderstandings during interviews to ensure high-quality data. Supervisors were additionally trained on how to troubleshoot standard technical issues with tablets. The

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: include the rice price — which appears with the wrong sign but is only marginally signiﬁcant — and elevation and population density — which are no longer signiﬁcant. Comparing Tables 7 and 5, we ﬁnd that in the smaller NLSS 2002 / 3 dataset none of the anticipated consumption variables is statistically signiﬁcant. Other results are as before. 4. 4 Magnitude To assess the relative magnitude of our results, we multiply coeﬃcients estimated in Tables 4 and 5 by the standard deviation of their respective regressors. We then average over the various regressions reported in Tables 4 and 5. Calculations are summarized in Table 8. The larger the value, the more inﬂuence the regressor has on the choice of a destination district. We see that the most important regressors in terms of magnitude are travel time to the near- est road, elevation, language similarity, and the price of rice. Consumption variables have an eﬀect on migration destination that is smaller in magnitude: a one standard deviation increase in anticipated relative consumption, for instance, has an eﬀect on destination that corresponds to a third of the eﬀect of a one standard deviation in elevation — and one-sixth of a one stan- dard deviation in distance from the nearest road. Income variables have a negligible eﬀect on migration decisions.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: 2 INTRODUCTION In 2015, an estimated 2. 2 million Syrians Under Temporary Protection (SUTPs) were residing in Turkey, the majority arriving in the country over the last 4 years. 2 Turkey ’ s national population is roughly 75 million; recent refugees account for approximately 3 percent of the population. For a country that has never experienced such a large-scale, sudden inflow of foreigners, demographic changes in the composition of the population and labor force will yield unprecedented implications. This paper examines, as data allows, the relationship between the size of the foreign-born population and host community poverty rates in Turkey. First, this paper finds the poverty rates of ‘ recent migrants ’ near the Syrian border (NSB) significantly increased from 2009 to 2013. Second, the number of foreign-born households being captured by the Labor Force Survey (LFS) is expanding, which suggests a growing number of foreign households that are likely to be Syrians. Third, with respect to poverty, the results show no negative impacts on the host community as a result of the increasing size of the foreign-born population. The impact of SUTPs has been both positive and negative. Overall, a significant negative impact on host communities ’ welfare is not observed in the data. Usage context: supporting mention, background mention, primary mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: humanitarian emergencies and protracted refugee status. Forced displacement is a pressing issue in the country, a result of conflict, drought, flood, economic instability, and political instability in neighboring countries (Martin, 2010; UNHCR, 2020d; IPCC, 2019). As of year-end 2023, more than 922,000 refugees and asylum seekers 1. Introduction 0 200,000 400,000 600,000 800,000 1,000,000 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Population Years Sudan Somalia South Sudan Eritrea Kenya Other countries Figure 1.1: Refugees and asylum seekers in Ethiopia by country of origin, 1984-2023 Source: UNHCR Refugee Data Finder 2024. Introduction 2 were seeking refuge in Ethiopia, with the majority originating from South Sudan (420,000), Somalia (280,000), Eritrea (170,000), and Sudan (49,000). Ethiopia is a signatory to the 1951 UN Convention on the Status of Refugees and its 1967 Protocol, with an obligation to protect refugees and asylum seekers. Most refugees (92 percent) are living in approximately 30 camps and sites located in Afar, Amhara, Benishangul-Gumuz, Gambella, Somali, and Tigray regions, with an increasing number of refugees

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: Figure 2. Location of Households in the VenReP-Kids Sample Notes: The figure depicts the exact geographic location of all the households in the VenRePs-Kids study. Green and blue dots depict the location of Colombian and Venezuelan households, respectively. The map in the upper right corner illustrates the location of Medell ´ ın (blue pin) with the department of Antioquia (highlighted in red). survey focuses on strata 1 through 4, intentionally omitting strata 5 and 6 to avoid bias toward higher-income groups which are less likely to include migrants in need of sup- port. 14

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: 9 this oversubscribed list. Selection into the training group was based on a “ vulnerability score ” that gave priority to younger, female and unemployed individuals. Despite this approach, intake was “ fuzzy ”- participants were ordered by their vulnerability score, with the most vulnerable entering up until capacity. In some intakes, individuals with comparatively high scores were not taken into the program. In others, individuals with comparatively low scores were included. We construct our treatment and control groups from these intake decisions. Data were collected from members of the host and refugee communities in each country. 4 In both Jordan and Lebanon, the intervention was implemented on a rolling basis. As soon as one training cycle was completed, another would begin. Data were collected in three waves during each training cycle. First, during an “ outreach ” phase, where data were collected in order to assign treatment status. Second, at “ baseline ”, which occurred before the training had begun but after treatment assignment was known. Third, data were collected at “ endline ”, immediately following the end of the training. Data collection for those assigned to the treatment and control followed the same pattern. 5 Outreach and baseline data collection took place less than a week apart and were collected between July 2018 and September 2019.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: We have constructed two different variables that try to account for the degree of severity of the conflict. 10 The first variable identifies individuals belonging to households that were displaced due to the 1999 wave of violence (all members displaced). The second variable identifies individuals in households that report having their house completely destroyed by the violent attacks in 1999. The TLSS 2001 contains also useful retrospective information on school attendance and grade attained across three different academic years: 1998 / 99, 1999 / 00 and 2000 / 01. We are 7 Commission for Reception, Truth and Reconciliation & Benetech Human Rights Data Analysis Group. ― Human Rights Violations Database. ‖ 9 February, 2006. Website: http: / / www. hrdag. org / resources / timor-leste_data. shtml. 8 There may be potential sample biases in the statement taking procedure given the voluntary nature of the process. It is possible that those living in more remote or mountainous areas, those living far away from the areas where the statements were taken, the sick, old and disabled and those with no access to the media or means of mass communication have a lower probability of being part of the sample. By contrast, those more active in local communities are more likely to have provided a testimony.

Human Rights Violations Database
TLSS 2001

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: 5 does not have migration or geographic identifiers. The SILC contains geographic identifying variables, (at the NUTS1 level) but still lacks migration variables. The data set this study uses is the Labor Force Survey (LFS) since there is an adequate availability of both migration and geographic variables. The LFS is representative at the NUTS2 level which corresponds to 26 regions in Turkey. One caveat is that income in the LFS refers to only wage income from employment, 9 and is an insufficient measure of income that should be used for welfare measurement. For example, important sources of income such as social assistance, asset liquidation, or remittances are missing. Therefore, income in the LFS is imputed with a few assumptions using information from the SILC. The NUTS1 spatial effects of the SILC are a good proxy for NUTS2 welfare dynamics in the LFS which increases the accuracy of the imputation model. However, since the original sample frame of the LFS does not account for the recent influx of foreign migrants in Turkey, the labor market characteristics of recent migrants might not be representative of the actual SUTP population. Therefore, results of the imputation could be interpreted as upper bound estimates for recent migrants. More details of survey techniques used to complete this exercise are available in the Annex.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: most land cover by built-up and shops, and nearest to Zone capital city, respectively. All estimates are controlled for refugee camps. Standard errors in parentheses. +p<0.10, * p<0.05, ** p<0.01, *** p<0.001 Variables Basic Model Local Market Proximity Market access Model I Model II Model I Model II Annexes 119 Table D.16: Proximity and market accessibility effects on engagement in agriculture activity: logit model Variables Proximity Market access Model I Model II Individual feature Male 0.1979*** 0.2016*** 0.1998*** (0.0289) (0.0286) (0.0297) Age -0.0307*** -0.0294*** -0.0296*** (0.0083) (0.0081) (0.0088) Age squared 0.0004*** 0.0004*** 0.0004** (0.0001) (0.0001) (0.0001) Some primary -0.1403*** -0.1436*** -0.1484*** (0.0305) (0.0298) (0.0307) Household feature HH size: member age [15,29] -0.0157 -0.0171 -0.0186 (0.0118) (0.0113) (0.0117) HH size: member age (30,44] 0.0422* 0.0414* 0.0320+ (0.0179) (0.0178) (0.0185) HH size: member age (45,64] 0.0187 0.0278 0.0314 (0.0221) (0.0226) (0.0237) HH access electricity -0.2980** -0.2655** -0.2658** (0.0929) (0.0884) (0.0974) Proximity and market access Level two 0.2065*** (0.0607) Level three 0.2358** (0.0788) Level four 0.3559*** (0.0769) Distance to Zone city (Km) 0.0022*** (0.0006) Market accessibility indicator -0.0792* (0.0330) Observations 742 737 742 Chi-square test 0.0000 0.0000 0.0000 R2 0.2517 0.2435 0.2128 Source: World Bank Staff based on SESRE 2023. Standard errors in

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: 33 recommendations (Jewkes, 2000). Their efforts contributed to the Employment of Educators Act and new Department of Education guidelines, both of which were introduced in 2000. These regulations mandate dismissal of educators found guilty of sexual or physical assault, or of having a sexual relationship with a student. They also define penalties for failing to report abuse. It remains to be seen whether these measures will have the intended impact. After the act was passed, Human Rights Watch (2001) suggested that the South African government needed to do more to increase awareness of the law among school principals and to strengthen enforcement. Institutional reform Efforts to improve the institutional response to gender-based violence range from sensitization and training of staff, sexual harassment policies, curriculum reform, school-wide anti-violence awareness campaigns, counseling and referrals, and broader efforts to reduce discrimination against girls and improve school safety. Initiatives to increase female enrolment by improving girls ’ safety at and on the way to school As mentioned earlier, parental concerns about girls ’ safety in school appears to lower female school enrolment in settings such as South Asia, Africa and the Middle East. Usage context: supporting mention, background mention, primary mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: The MPI can be decomposed by any groups for which the data are representative and broken down by indicator to show the composition of multidimensional poverty, adding to the policy relevance of the analysis. To tackle individual-level and intrahousehold analyses, we build on the work of Alkire, Ul Haq and Alim (2019). The focus is on individual deprivations, and we call the persons with individual-level data in each indicator the eligible household members. For example, children aged 6-16 years might be eligible for deprivations in terms of school attendance, but not those older or younger. For individual-level indicators, we identify who and how many household members are deprived: their gender and their age, and what proportion of eligible household members are deprived. This is a powerful and potentially informative steppingstone for analysis. Consider two households, each of which has five eligible members with data on nutrition. The aggregation rule in this example is that if any household member is undernourished then the household is undernourished. So, both households are deprived in terms of Usage context: background mention, supporting mention, primary mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: required to purchase other basic staple foods such as salt and vegetables. Given that the WFP provisions are the only reliable rations that refugees receive, we approximate a cash transfer of 450 taka per week to at least double potential weekly consumption. Relative to the wealth refugees possess, 450 taka per week is likewise sizeable: average baseline savings is 195 taka, with the median refugee reporting zero taka in savings. Average baseline borrowing (typically in the form of store credit) is 1, 600 taka, with a median of 600 taka. Refugees have no economically meaningful assets that may be more common among the rural poor, such as land or cattle, given the unanticipated displacement which forced them from their homes. Relative to other employment opportunities, average reported pay is 300 taka per day for less than three days. The monthly cash transfer is therefore more than double what a refugee might expect from alternative employment if he or she is fortunate enough to secure a job. 4 Data Collection and Survey Instruments Timeline and survey instruments We collected data via a baseline, commencing in November 2019, and endline survey, commencing in February 2020, as well as seven midline surveys conducted prior to payment disbursal each week. These weekly surveys collected a small subset of well-being outcomes.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input:
REFERENCES

Bagenda E, Naggaga A and Smith E (2003), Land problems in Nakivale refugee
settlement and implications for refugee protection in Uganda, Refugee Law Project
working paper No. 8, Makerere University, Kampala Uganda.

Crisp Jeff (2002) ‘No solution in sight: the problem of protracted refugee situations in
Africa,’ paper prepared for a symposium on the multidimensionality of displacement
in Africa, Kyoto Japan.

DFID (2001), Sustainable livelihoods guidance sheets, London, United Kingdom.

Harrell-Bond, B (1986), Imposing aid: Emergency assistance to refugees New York:
Oxford University press.

Hajabakiga Patricia (November, 2004), “Addressing land issues in post conflict
settings: the case of Rwanda”, paper presented at a conference on a theme Land in
Africa: market asset or secure livelihood, London.

Harrell-Bond, B (2002) ‘Towards the economic and social ‘integration’ of refugee
populations in host countries in Africa’, paper presented at an International
conference on protracted refugee situations in Africa, Entebbe Uganda.

Holborn W. Louise (1975) Refugees a problem of our time: the work of the United
Nations High Commissioner for Refugees, 1951-1972, Vol. II Metuchen N.J: The
Scarecrow Press, Inc pp 1213-1258

Jacobsen, K (2001) ‘The forgotten solution: local integration for refugees in
developing countries’, New issues in refugee research, working paper no. 45,
UNHCR, Geneva

Johns Richard (2003), Participatory Poverty Assessment of Nakivale and Oruchinga
Refugee Camps in Southern Uganda: Livelihood Characteristics, Economic
Constraints and Recommendations for Change, UNHCR and the Economic and Social
Research Council, UK.

Kabeer Naila (1994) Reversed realities: Gender hierarchies in Development thought,
London: Verso.

Kalyango Ronald and Huff Kirk (2002) Refugees in the city: status determination,
resettlement and the changing nature of forced migration in Uganda, Refugee Law
Project Working paper No. 6, Kampala Uganda.

Kasfir Nelson (1988), ‘Land and peasants in Western Uganda: Bushenyi and Mbarara
Districts.’ In Hansen Holger B and Twaddle Michael (Eds.) Uganda Now: between
decay and development, London: James Carrey Limited.

Kalyango Ronald (forth coming), Interfaces of care, institutional policies and
livelihood strategies of refugee women in Uganda.

Kibreab, G (1989), ‘Local settlements in Africa: a misconceived option?’ Journal of
Refugee Studies 2(4):468-490.

11


Input:
## INTRODUCTION
#### This report is mainly based on the results of the survey about intentions, challenges and obstacles encountered during participation in the compensation programme for damaged/destroyed housing objects launched within CMU resolution №767. In addition, a significant deal of information was gathered during our monitoring visits to plenty of settlements in Donetska and Luhanska oblasts in the period of October-December. Our outreach workers and legal team also took part in some of the commission assessment sessions either as observers or members, thus they had an opportunity to obtain firsthand experience on the implementation of the programme. By focusing on the perspective of claimants, this report complements a survey conducted by UNHCR in November 2020, which focuses on the functioning of the local assessment commissions, based on observations from R2P and other NGO members or observers in these commissions. R2P launched this survey primarily to find out whether this programme is relevant for its target audience, as well as to reveal the pitfalls of the programme from the perspective of participants. Therefore, we decided to survey our beneficiaries of IDP and conflict-affected background who reportedly had problems with damaged/destroyed housing objects and those potential beneficiaries whom our outreach workers already knew or got to know during field trips. The survey has been conducted in the period of October-November in Donetsk and Luhansk oblasts via phone and face-to-face interviews. Besides, upon the completion of the survey, some cases were directed to R2P legal team for further investigation. As a result, our team not only conducted research but also promptly provided assistance to those who were willing to participate in the programme but for some reason experienced difficulties with applying for monetary compensation/assistance.

This publication has been produced with the assistance of the UN Refugee Agency (UNHCR). The

contents of this publication are the sole responsibility of «Right to Protection» and can in no way

be taken to reflect the views of UNHCR.

3


Input: IPF Investment Project Financing KEMSA Kenya Medical Supplies Authority KISEDP Kalobeyei Integrated Socio-Economic Development Plan 2 KHIS Kenya Health Information System KHSSP Kenya Health Sector Strategic Plan KISEDP Kalobeyei Integrated Socio-Economic Development Plan LMP Labor Management Plan M&E Monitoring and Evaluation MoH Ministry of Health MPDSR Maternal and Perinatal Death Surveillance and Response MWMP Medical and Waste Management Plan NCCF National Climate Change Framework Policy NCCRS National Climate Change Response Strategy NCD Non-Communicable Disease NDC Nationally Determined Contribution NHIF National Health Insurance Fund NT National Treasury OAG Office of the Auditor General O&M Operations and Maintenance OP Operational Policy ORS Oral Rehydration Salts PA Project Account PAD Project Appraisal Document PFM Public Financial Management PHC Primary Health Care PDO Project Development Objective PMT Project Management Team PNC Postnatal Care POM Project Operations Manual PP Procurement Plan PPH Postpartum Hemorrhage PPSD Project Procurement Strategy for Development PS Principal Secretary QoC Quality of Care RMNCAH Reproductive, Maternal, Newborn, Child, and Adolescent Health SEA / SH Sexual Exploitation and Abuse / Sexual Harassment SEP Stakeholder Engagement Plan SDPHS State Department for Public Health and Professional Standards SHA Social Health Authority SHIF Social Health Insurance Fund SPA Special Purpose Account STEP Systematic Tracking of Exchanges in Procurement STEPS STEPwise Approach to NCD Risk Factor Surveillance THS-UCP Transforming Health Systems for Universal Care Project


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**Components**

**Component Name** **Cost (US$)**

Strengthening institutional capacity for health service delivery towards 55,000,000.00 achieving UHC Improving utilization of quality health services at primary care level 150,000,000.00 Project management and evaluation 10,000,000.00 @#&OPS~Doctype~OPS^dynamics@padborrower#doctemplate

**Organizations**

Borrower: Republic of Kenya Implementing Agency: Ministry of Health @#&OPS~Doctype~OPS^dynamics@padfinancingsummary#doctemplate

**PROJECT FINANCING DATA (US$, Millions)**

**Maximizing Finance for Development**

**Is this an MFD-Enabling Project (MFD-EP)?** No

**Is this project Private Capital Enabling (PCE)?** No

**SUMMARY**

**Total Operation Cost** **215.00**

**Total Financing** **215.00**

**of which IBRD/IDA** **200.00**

**Financing Gap** **0.00**

**DETAILS**

**World Bank Group Financing**

International Development Association (IDA) 200.00 IDA Credit 160.00 IDA Grant 40.00

**Non-World Bank Group Financing**

Trust Funds 15.00 Page 2 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**SYSTEMATIC OPERATIONS RISK- RATING TOOL (SORT)**

**Risk Category** **Rating**

1. Political and Governance   Moderate

2. Macroeconomic  Substantial 3. Sector Strategies and Policies  Moderate 4. Technical Design of Project or Program  Moderate 5. Institutional Capacity for Implementation and Sustainability  Moderate 6. Fiduciary  Substantial 7. Environment and Social  Moderate 8. Stakeholders  Moderate 9. Other  Substantial 10. Overall  Moderate @#&OPS~Doctype~OPS^dynamics@padcompliance#doctemplate

**POLICY COMPLIANCE**

**Policy**
Does the project depart from the CPF in content or in other significant respects?

[ ] Yes [ ] No ✓ Does the project require any waivers of Bank policies?

[ ] Yes [ ] No ✓

**ENVIRONMENTAL AND SOCIAL**

**Environmental and Social Standards Relevance Given its Context at the Time of Appraisal**

**E & S Standards** **Relevance**

ESS 1: Assessment and Management of Environmental and Social Risks and Relevant Impacts ESS 10: Stakeholder Engagement and Information Disclosure Relevant ESS 2: Labor and Working Conditions Relevant ESS 3: Resource Efficiency and Pollution Prevention and Management Relevant Page 4 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**I.** **STRATEGIC CONTEXT**

**A. Country Context**

1. **The Kenya economy has continued to recover from the impacts of the COVID-19 pandemic, but the growth has**
**slowed down in the last year.** Real gross domestic product (GDP) increased by 4.8 percent in 2022, a decrease from 7.5
percent annual growth in 2021, largely due to the weather shocks experienced in the last two years, domestic macroeconomic policies, and challenging global conditions. [1] The economy is expected to grow by 5.0 percent in 2023 and 5.2 percent on average in 2024-2025, higher than the pre-pandemic average of 5.0 percent in 2010-2019. While growth prospects remain optimistic, the economy remains vulnerable to shocks such as drought, rising inflation and food insecurity.

2. **Kenya is highly vulnerable to climate change, particularly extreme floods, and droughts, which has affected**
**food security for millions of people particularly in the arid and semi-arid north and north-east of the country** . [2] Floods
are the most significant and frequent climate-related hazard in Kenya making up 40.0 percent of all-natural hazards from 1980-2020. [3 ] Flooding is particularly impactful to communities around Kenya’s lakes and waterways. For example, a 2021 United Nations (UN) report [4] projected climate change induced flooding may cause the expansion of Lake Turkana, displacing communities while impinging on agriculture and livelihoods. Simultaneously, drought is likely to adversely affect the country’s agriculture sector, which is predominantly dependent on seasonal rains and is expected to negatively impact the economy and food security, reversing the gains in health and nutrition outcomes. Since 2015, Kenya has experienced a steady increase in the prevalence of severe food insecurity from 15.0 percent to 26.1 percent. [5] Between July and September 2022, an estimated 3.5 million people (24.0 percent of the Kenya population in arid-and semi-arid counties) experienced acute food insecurity. [6] 3. **For more than three decades, Kenya has been home to a significant population of refugees and asylum seekers.** There are 691,868 refugees and asylum seekers in the country, including in cities such as Nairobi, Mombasa, Nakuru, and Eldoret, but the majority live in two designated refugee camps [7] - with 320,572 in Dadaab Camp in Garissa County and 271,995 in Kakuma Camp and Kalobeyei Settlement in Turkana County. [8] The two camps are under the management of the Government of Kenya’s Department of Refugee Services (DRS), with support from the United Nations High Commissioner for Refugees (UNHCR) and humanitarian partners who provide operational support and humanitarian assistance, including primary and secondary health and nutrition services. The Government has demonstrated its commitment to the Global Compact on Refugees by enacting the Refugees Act of 2021, which grants refugees more rights and protections, and by supporting the Shirika Plan, [ 9] which seeks to create integrated settlements where refugees can live, access social services, and work alongside Kenyans.

**B. Sectoral and Institutional Context***

1 Kenya Economic Update, June 2023 2 World Bank, Climate Change Knowledge Portal 3 World Bank Climate Change Knowledge Portal - Kenya.https://climateknowledgeportal.worldbank.org/country/kenya/vulnerability 4 United Nations Environment Program: “Climate change could spark floods in world’s largest desert lake: new study”, 2021.

5 World Bank data. Prevalence of food insecurity in the population – Kenya **Error! Hyperlink reference not valid.** 6 Kenya: IPC Acute Food Insecurity and Acute Malnutrition Analysis (July - December 2022) 7 For a detailed map see: https://data2.unhcr.org/en/country/ken 8 UNHCR Statistics package. Kenya registered refugees and asylum seekers (31 July 2023) 9 The Shirika Plan is a Government of Kenya socioeconomic development plan outlining the transition from refugee encampment to integrated settlements.

Page 9 of 43

World Bank Climate Change Knowledge Portal


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) 4. **The health status of Kenyans has improved in the last five years, but significant geographic and socioeconomic**
**inequities remain, affecting women and children.** The life expectancy of Kenyans has improved from 63 years in 2013 to
67 years in 2020 but fell to 61 years in 2021 owing to the COVID-19 pandemic. [10] Under-five and infant mortalities dropped from 52 and 39 deaths per 1,000 live births in 2014 to 41 and 32 in 2022, respectively, partly due to improved coverage of primary healthcare services and significant progress in malaria and HIV/AIDS response. [11] Despite the number of women delivering under the care of a skilled health worker increasing significantly, challenges remain around neonatal mortality, which is high at 21 deaths per 1,000 live births in 2022: a marginal decline from 22 per 1,000 live births in 2014. Similarly maternal mortality remains high at 342 maternal deaths per 100,000 live births, [12] suggesting challenges related to quality of care (QoC). Teenage pregnancy declined only slightly from 18.0 percent in 2014 to 15.0 percent in 2022. While the country has recorded improvements in childhood nutrition, 18.0 percent of children aged below 5 years are stunted, a decline from 26.0 percent in 2014. Despite improvements in coverage and utilization of health care services, especially for maternal and child health, geographic and socioeconomic inequities remain. Although 89.3 percent of pregnant women deliver under the care of a skilled health worker, five counties reported skilled delivery below 66.0 percent (Turkana-53.0 percent; Mandera-55.0 percent; Wajir-57.0 percent; Samburu-57.0 percent; Tana River-59.0 percent). Wider gaps are reported for utilization of antenatal care (ANC), with only 32.1 percent of women in Garissa County attending at least 4 ANC visits, compared to 82.2 percent in Nyeri County. Only 53.9 percent of women from the lowest wealth quintile attended at least 4 ANC visits compared to 82.0 percent of women from the highest wealth quintile.

5. **In Garissa and Turkana counties, refugees and their host communities face barriers to healthcare services,**
**mostly affecting women and children.** Garissa and Turkana counties record the lowest percentages of women receiving
at least 4 ANC visits (31.2 percent) in 2022 and deliveries by a skilled provider (52.6 percent) respectively. [13 ] In the refugee camps, most health services are provided by UNHCR and non-governmental organizations in collaboration with the Government. The overcrowded conditions, clean water supply shortages and hygiene challenges present heightened risks of communicable disease outbreaks such as cholera. Other recent outbreaks in the refugee camps include polio, dengue fever, and chikungunya. Refugees and host communities have also been affected by prolonged drought in the region and the food security of refugees has been further affected by cuts in the general food assistance. From 2020 to July 2022, there has been a steady and significant increase in malnutrition cases across all refugee camps, with children under 5 years being particularly affected by malnutrition and micronutrient deficiencies. [14] 6. **The devolution of health service delivery in 2013 has presented mixed results** . Decentralization of responsibility for public sector health service delivery to the 47 county Governments has been accompanied by a 34.0 percent increase in the number of facilities, a 46.0 percent improvement in public health worker density between 2014 and 2020, and many counties have equipped their health facilities to respond to the evolving health needs. County Governments are also exploring approaches to strengthen primary care service delivery through governance and financial management reforms, such as the Facility Improvement Fund. However, county Governments have faced significant challenges in management of human resources for health, ensuring availability of Health Products and Technologies (HPTs), improving quality of care,

[10 World Bank Estimates: https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=KE](https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=KE) 11 Kenya Demographic Health Survey, 2022. Key Indicators Report 12 Ministry of Health Kenya (2020) Kenya Progress Report on Health and Health-Related SDGs.
13 Kenya Demographic Health Survey, 2022 14 UNHCR & WFP, Joint Assessment Mission Kenya-Refugee Operations (2022) Page 10 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) and facilitating effective governance of health facilities to deliver comprehensive networked primary care. [15,16,17,18] Stockouts of essential medicines persist and access to essential diagnostics remains low with only 17.0 percent of facilities assessed as having a full set of basic diagnostic items. [19] 7. **The Government initiated various reforms aimed at strengthening capacity of the National Health Insurance**
**Fund (NHIF) and the Kenya Medical Supplies Authority (KEMSA).** Both institutions play a critical role in Kenya’s universal
health coverage (UHC) agenda. NHIF reforms include changes to governance arrangements, re-engineering business processes, modernization, and realignment of the information and communications technology, modification of provider payment mechanisms and payment systems among others. To fast-track progress towards UHC, the Government introduced four laws in October 2023 (Social Health Insurance Act, Primary Health Care Act, Facility Improvement Financing Act, and the Digital Health Act). Under the new health financing arrangement, all Kenyan citizens and residents will be required to be members of the Social Health Insurance Fund (SHIF). Primary health care will be purchased through the primary care fund and financed through tax allocation by the national Government. Additionally, management of chronic illnesses and health emergencies will be through the emergency, chronic and critical illness fund, which will be drawn upon once a member has exhausted their SHIF benefits. The Government is in the process of developing the regulations and implementation arrangements to operationalize these Acts. Key issues in KEMSA relate to: (a) inadequate funding to stock commodities leading to long turnaround times; (b) suboptimal use of information systems in procurement processes; (c) weak business processes; (d) weak governance; (e) weak human resource realignment; (f) outdated Enterprise Resource Planning (ERP) system; and (g) weak credit control systems among others. Significant progress has been made in implementing reforms to address these challenges, however major gaps remain. The World Bank continues to provide technical support, but operational support is required for KEMSA to function efficiently.

**C. Relevance to Higher Level Objectives**

8. **The project is fully aligned with the World Bank’s mission and the Regional priorities** by contributing to increasing the number of people receiving essential health services in Kenya. **The project is strongly aligned with the**
**World Bank Group’s (WBG) FY23-28 Country Partnership Framework (CPF) for Kenya, discussed by the Board of**
**Executive Directors on November 22, 2022 (Report No. 172255) and Government health sector priorities.** Objective 2 of
the CPF aims to “improve public expenditure transparency and efficiency”, a focus of the project. The CPF also aims for “greater equity in service delivery outcomes”, which will be achieved partly through reducing disparities in health outcomes (objective 4). The project is also aligned to objective 6, “increase household resilience to, and national preparedness for shocks”, highlighted in the CPF through the need to increase access to social health insurance, improving access to quality health care services and expanding UHC reforms. In addition, the project will directly contribute to the priorities identified in the Kenya Health Policy 2014-2030, the Kenya Health Sector Strategic Plan (KHSSP, 2018-2023), the Kenya UHC Policy (2020-2030), and the Kenya Health Financing Strategy (2020-2030).

15 Waithaka, D., Kagwanja, N., Nzinga, J. et al. Prolonged health worker strikes in Kenya- perspectives and experiences of frontline health managers and local communities in Kilifi County. Int J Equity Health 19, 23 (2020).
16 Nyawira, L., Tsofa, B., Musiega, A. et al. Management of human resources for health: implications for health systems efficiency in Kenya. BMC Health Serv Res 22, 1046 (2022).
17 McCollum R, Limato R, Otiso L, et al. Health system governance following devolution: comparing experiences of decentralisation in Kenya and IndonesiaBMJ Global Health 2018;3:e000939 18 Kairu, A., Orangi, S., Mbuthia, B. et al. Examining health facility financing in Kenya in the context of devolution. BMC Health Serv Res 21, 1086 (2021).
19 Ministry of Health Kenya Harmonized Health Facility Assessment 2018-19. The diagnostic tests were: HIV, malaria, and syphilis rapid test; urine test for pregnancy; blood glucose; urine dipstick for glucose and protein; and hemoglobin levels Page 11 of 43

Kenya Harmonized Health Facility Assessment


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) 9. **The project is consistent with Kenya’s Nationally Determined Contribution (NDC, updated 2020)** **[20]** **[21]** **, the**
**National Climate Change Framework Policy (NCCF, 2016) and National Climate Change Response Strategy (NCCRS,**
**2010).** The project is anticipated to have a considerable contribution to improving climate adaptation and resilience in the
country and is not anticipated to contribute to greenhouse gases emissions. Kenya’s climate policies emphasize key actions which the project supports including: integration of climate change adaptation into county level development planning; improving resilience of vulnerable populations to climate-related shocks; addressing vector-borne disease transmission (malaria, dengue), water-borne disease outbreaks, food insecurity and malnutrition; reducing direct injuries and mortality; and minimizing damage to infrastructure. Further, the Kenya Health Policy (2014) and KHSSP [22] acknowledge the role of climate change in increasing the burden of disease in the country. [23] 10. **The World Bank, following consultation with UNHCR, confirms that the protection framework for refugees** **[24]**
**continues to be adequate in Kenya for accessing financing from the IDA20 Window for Host Communities and Refugees**
**(WHR).** Kenya’s treatment of refugees is governed by the Refugees Act of 2021 and is largely in line with the international
and regional refugee protection standards and Kenya’s commitments under the Global Compact on Refugees. The Act recognizes the rights of refugees to participate in economic and social development and supports refugee inclusion in national and county development planning. In 2023, the second phase of the Kalobeyei Integrated Socio-Economic Development Plan 2 (KISEDP) and the Garissa Integrated Socioeconomic Development Plan (GISEDP) were launched, which highlight the key role being played at the County level to support local solutions that benefit refugees and host communities, including in the health sector. In its IDA20 WHR Strategy Note, the Government identified as a priority supporting social services needs in health and addressing the health priorities outlined in the KISEDP and GISEDP. The Refugee Regulations, to operationalize the Refugees Act of 2021 are in the final stages of development and are due for publication. The regulations will provide clarity in the Act’s operationalization, which will strengthen the protection framework. In September 2023, Kenya gazetted Legal Notice No. 143 of 2023, recognizing refugee identification documents for the purposes of acquiring services provided by the Government, including health. The Shirika Plan, which is currently under development, is a multi-sectoral plan that delineates development solutions that benefit both refugees and host communities through an integrated service delivery approach, building on the KISEDP and GISEDP. The Ministry of Health (MoH) is involved in the Plan’s drafting and this operation will ensure close alignment of refugee health policy priorities and county level implementation.

**II.** **PROJECT DESCRIPTION**

**A. Project Development Objective (PDO)**

**PDO Statement**
11. To improve utilization and quality of primary healthcare services and strengthen institutional capacity for service delivery.

20 Government of Kenya. (April, 2010) National Climate Change Response Strategy.
21 Government of Kenya (2016). National Climate Change Framework Policy. Accessed.
22 Government of Kenya (2018) Kenya Health Sector Strategic Plan.
23 Ministry of Health (July, 2014) Kenya Heath Policy 2014-2030.
24 Based on UNHCR’s Kenya Refugee Protection Assessment Update No. 5 from January to June 2023.

Page 12 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**PDO Level Indicators**
12. The PDO level indicators are: (a) Percentage of women receiving postnatal care within 48 hours, including in refugee hosting counties; (b) Percentage of children immunized with three doses of Pentavalent vaccine; (c) Percentage of pregnant women attending 4 or more ANC visits, including in refugee hosting counties; (d) Proportion of Children Under 5 with diarrhea treated with Zinc/ORS Co-Pack; (e) Order fill rate for priority health products and technologies (HPTs); (f) order turnaround time.

**B. Project Components**
13. The project will comprise three Components focusing on both the national and county level, with clear linkages between the two levels of Government.

14. **COMPONENT 1: STRENGTHENING INSTITUTIONAL CAPACITY FOR HEALTH SERVICE DELIVERY TOWARDS**
**ACHIEVING UHC (US$55 million)** : Component 1 will focus on (a) strengthening the institutional capacity of KEMSA and
availability of HPTs; (b) supporting health financing reforms; and (c) improving availability and use of quality data for decision making.

15. **Sub-component 1.1: Institutional and operational reforms to enhance efficiency and transparency of KEMSA**
**(US$30 million):** This sub-component will support: (a) building up buffer stocks in KEMSA to ensure timely availability of
HPTs at primary care level, thus increasing the order-fill rate, reducing the order turn-around time, and promoting efficiency. Funds will be earmarked for the procurement and distribution of HPTs for primary care services (levels 1-3) in all 47 counties during the life of the project. Counties will draw down HPTs from an agreed list, based on their resource allocation as described in sub-component 2.1. To ensure transparency and accountability in the procurement process, an HPT governance committee incorporating key stakeholders will be established. Climate sensitive planning for HPTs distribution will be included; (b) automation of the procurement processes, through rolling out a new ERP system with extended supply chain modules to ensure end-to-end visibility; and (c) strengthening governance and accountability, including development and implementation of an accountability dashboard that provides visibility of the procurement process and distribution of HPTs to various stakeholders. The project will use seasonal data to inform pharmaceutical planning for climate sensitive conditions (e.g., malaria, cholera, anti-diarrheal medicines, etc.). The Directorate of HPTs, MoH will work closely with KEMSA to ensure maximum efficiency in implementation of this sub-component.

16. **Sub-component 1.2: Health financing and quality of care reforms (US$15 million):** This sub-component will support the recently introduced Government UHC reforms, including but not limited to the transition from the NHIF to the Social Health Authority (SHA). Areas of support include development of regulations and implementation roadmaps, design and rationalization of a benefit package, developing a framework for review of the benefit package including strengthening capacity for the health technology assessment, design of business processes and claims processing, stakeholder engagement among others. Additionally, the project will support the MoH to establish/strengthen regulatory bodies and operationalize quality of care reforms for improved strategic purchasing.

17. **Sub-component 1.3: Improve availability and use of quality data for decision making (US$10 million):** This subcomponent will support the Government to improve generation and use of strategic information for decision making, specifically through conducting relevant cross-sectional surveys including, but not limited to, the WHO STEPwise approach to non-communicable diseases (NCD) risk factor surveillance (STEPS) survey, and the Household Health Expenditure and Utilization Survey. Climate sensitive planning for surveys will be used and questions on climate and health impacts will be included in the survey to generate relevant data to inform decision making. Support will also be provided towards dissemination of findings to the lowest level.

Page 13 of 43

Household Health Expenditure and Utilization Survey


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) quality of care committees (e.g., the Maternal and Perinatal Death Surveillance and Response (MPDSR) committees); (e) support for quality monitoring activities; and (f) demand generation activities.

22. **Sub-component 2.3: Improving access to and utilization of quality health services in refugee camps and host**
**communities in Garissa and Turkana Counties (US$40 million):** The Sub-component aims to address the barriers to
accessing and utilizing quality services in refugee camps and their host communities in Garissa and Turkana counties. More specifically, the Sub-component will support: (a) strengthening community health services; (b) improving availability of essential HPTs for services at levels 1-4 (level 4 is the sub-county hospital); (c) improving the availability of energy efficient diagnostic and medical equipment; (d) training of community enrolled health nurses through the Kenya Medical Training College; (e) recruitment of health workers; (f) strengthening referral systems; (g) climate resilient and energy efficient renovation of health facilities; and (h) support towards management of the transition process of health facilities and health workers to County Governments. Analytical work and capacity support will be provided to the refugee hosting counties and DRS to support county planning and coordination with humanitarian stakeholders in the management of the transition of health services. Both counties will develop AWPs, under the County Integrated Development Plans focusing on the identified areas of support. This will build on counties’ refugee and host communities plans that include health priorities, the KISEDP and GISEDP.

23. **COMPONENT 3: PROJECT MANAGEMENT AND EVALUATION (US$10 million):** This Component will support project management activities at national and county level. Key areas of support will include (a) providing operational costs and logistical services for day-to-day management of the project; (b) project monitoring and evaluation activities; (c) environmental and social risk management; (d) stakeholder engagement; (e) fiduciary management; (f) contracting of staff on a need basis; (g) technical assistance and county peer-to-peer learning among others; and (h) development of a climate emergency plan at the national level, which will inform county level actions to reduce the risk of climate change on health service delivery activities. Counties will be encouraged to include relevant climate mitigation actions in their AWPs.

**C. Project Beneficiaries**

24. **The project will benefit all Kenyans;** however, the main beneficiaries are women and children from the poorest population who tend to utilize primary care services more, including refugees and host communities in Garissa and Turkana. The project will provide support to all 47 counties to address key priority areas that impact on primary health care (PHC) and focus on addressing inequities in counties that have poor RMNCAH service coverage and outcomes.
Strengthened health services will support the needs of about 1.8 million host community members in Garissa and Turkana (100 percent) and more than 590,000 refugees in these counties (100 percent).

Page 15 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**D. Results Chain**

**CHALLENGES** **ACTIVITIES** **OUTPUTS** **SHORT-TERM**
**OUTCOMES**

**CHALLENGES** **ACTIVITIES** **OUTPUTS** **SHORT-TERM** **PROJECT** **LONG-TERM**
**OUTCOMES** **OUTCOMES** **OUTCOMES**

**Component 1**
Suboptimal availability Finance key health surveys Improved availability of Improved and use of data for quality data evidence -based decision making decision making

**PROJECT**
**OUTCOMES**

Finance key health surveys Improved availability of quality data Improved evidence -based decision making A2 Improved (i) transparency, efficiency of KEMSA and (ii) availability of essential HPTs at the lowest levels A1 Improved delivery of quality PHC services, including in refugees hosting areas Improved utilization and quality of primary healthcare services and strengthened institutional capacity for service delivery, including for refugees and host communities Reduced mortality and morbidity, and greater human capital attainment Suboptimal funding, inefficiency, and lack of transparency at KEMSA Upgrade of ERP system at KEMSA Build up buffer HPTs stock in KEMSA

**Component 2**
Frequent stockouts of Procure and distribute HPTs, essential commodities including HPTs for NCDs at PHC level Low quality of maternal and child health services at PHC level Inequitable geographic health outcomes particularly for RMNCAH Shortages of skilled human resources for health (HRH) Parallel health services for refugees with limited county engagement Implement priority interventions at PHC facilities in all 47 counties Support processes to strengthen clinical quality of care related to RMNCAH services in selected counties Implement priority interventions in Garissa and Turkana, including refugee hosting areas (including support to HRH, renovations of health facilities) Improved functionality of the ERP system modules Increased number of orders received within required lead time Increased number of HPTs procured and distributed to health facilities Improved operations of health facilities, systems, and community health services Improved processes for quality clinical practices Improved availability and functionality of health facilities, community health units, including for refugees and host communities Assumptions: A1- Beneficiaries have access to system performance information; A2- Policy makers utilize information to improve project implementation.

25. **The above diagram presents the results chain.** The project aims to "improve utilization and quality of primary healthcare services and strengthen institutional capacity for service delivery”. This will be achieved by addressing key health challenges including inefficiencies at KEMSA leading to frequent stockouts of essential commodities at PHC level, inequitable geographic health outcomes, shortages of HRH, parallel health services for refugees with limited county engagement, and suboptimal availability and use of data. By investing in high impact activities the project will contribute towards improving delivery of quality PHC services and evidence-based decision making. The project is anticipated to contribute to increasing utilization of PHC services, quality of PHC services, and strengthening institutional capacity.
Specific PDO level indicators are detailed under paragraph 12.

**E. Rationale for Bank Involvement and Role of Partners**

26. **The World Bank has a solid track record in supporting Kenya’s health sector.** Over the years, the World Bank has supported several projects, including two regional operations: the East Africa Public Health Laboratory Networking Page 16 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**A. Institutional and Implementation Arrangements**

29. **The project will be implemented by multiple entities at both national and county level.** The MoH, through the State Department of Public Health and Professional Standards (SDPHS), will have the overall responsibility of overseeing implementation of the project. A project steering committee chaired by the Principal Secretary (PS) for the SDPHS, and including the PS National Treasury, PS State Department of Immigration and Citizen Services, Chief Executive Officer of the Council of County Governors, and the Solicitor General will advise the project. County Governments will be responsible for implementation of county-level activities under Component 2, with support from KEMSA for procurement and delivery of HPTs to primary care facilities. Counties may conduct procurement on a need-by-need basis for activities in the positive list (for Sub-component 2.2) and Sub-component 2.3. Both KEMSA and county Governments will put in place a management team to oversee project implementation. In refugee camps, implementation will be undertaken by relevant county Governments in close coordination with DRS and UNHCR.

30. **The Project Management Team (PMT) under the MoH, will have overall responsibility for the coordination and**
**implementation of the project.** The PMT will be headed by the Project Manager who will be responsible for the effective
functioning of the project. The MoH will be required to fully designate and maintain PMT members with appropriate skills, including Component coordinators, safeguards and fiduciary staff, and a M&E officer. The PMT will (a) coordinate the project activities; (b) ensure the financial management of all project activities in all Components; and (c) prepare consolidated AWPs, budgets, monitoring and evaluation, and quarterly and annual financial and technical implementation reports. The PMT will compile reports from each of the 47 counties and all national implementing entities and share them with the World Bank.

31. **Each county will designate and maintain for the project period:** (a) a Project focal point; (b) a head of the unit responsible for procuring HPTs; (c) an environmental specialist; (d) a social development specialist; (e) a monitoring and evaluation specialist; (f) a procurement officer (if required as indicated in the Project Operations Manual); and (g) a project accountant and internal auditor to support project’s financial management functions.

**B. Results Monitoring and Evaluation Arrangements**

32. **The M&E approach for the project is aligned with the Government’s procedures and data sources and will**
**contribute to improved data quality.** All project indicators (a) are a subset of the health sector’s performance indicators
available in various data sources including the Kenya Health Information System (KHIS); and (b) will be collected routinely through project reports. The project will support county health sector annual performance data review meetings as well as availability of key surveys under Component 1. Where relevant, at project closure, data from household and facility surveys will be used to complement routine data to measure project achievement of the PDO.

**C. Sustainability**

33. **The project will support priority interventions outlined in the national health strategies to ensure sustainability.** The project will build on existing national systems and structures for implementation and fiduciary arrangements. The Government remains committed to improving delivery of primary healthcare services to advance progress towards UHC, and key project activities are aligned with these objectives. The project implementation entities will be drawn from existing Government structures which will ensure continuity of the expected results beyond the project period. In addition, Page 18 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) separate bank account, financial reporting, and other financial management requirements; and (e) preparation of a POM with a detailed FM section to address FM aspects of the proposed project. These mitigation measures will provide reasonable assurance that the project resources will be used for the intended purposes.

**(ii)** **Procurement**
43. **Procurement Regulations:** Procurement activities under the project will be carried out in accordance with “The World Bank’s Procurement Regulations for IPF Borrowers, First published July 2016 and revised Fifth Edition September 2023”, hereafter referred to as “Procurement Regulations”; the World Bank’s “Guidelines on Preventing and Combating Fraud and Corruption in Projects Financed by IBRD Loans and IDA Credits and Grants (revised as of July 1, 2016) and other provisions to be stipulated in the project’s Legal Agreement with the Borrower.” 44. **A Project Procurement Strategy for Development (PPSD) has been prepared by the Borrower** to support the implementation and achievement of development objectives of the project and deliver Value for Money. The PPSD will form the basis for preparation of the Procurement Plan (PP), providing justification for procurement decisions including the selection methods and market approaches. The PP has been prepared for the first 18 months of project implementation and will be updated at least annually, or as required, to reflect the actual project implementation needs.

45. **Systematic Tracking of Exchanges in Procurement (STEP):** The project will use STEP, the World Bank’s online procurement planning and tracking tool to record all procurement actions including planning, updating, and clearing PP and seeking and receiving World Bank’s review and No Objection to procurement actions as needed and establish benchmarks, monitor delays, and measure procurement performance.

46. **Profile of Procurement Activities:** The key procurements of the project comprise of (a) Goods: purchase of buffer HPTs stock in KEMSA; Procurement and distribution of HPTs; (b) Non-consulting services: Upgrade of ERP system at KEMSA; (c) Works: Renovation of works under Component 2.3; and (d) Consulting Services: institutional reforms, key health surveys; project monitoring and evaluation activities; environmental and social safeguards related activities; fiduciary management, contracting of staff on a need basis; technical assistance etc.

47. **National Procurement Procedures:** The country’s own procurement procedures may be used when approaching the national market as agreed in the procurement plan. When the Borrower uses its own national open competitive procurement procedures as set forth in the Public Procurement and Asset Disposal Act 2015 (revised Edition 2022) and the attendant Regulations 2020 such arrangements shall be subject to the provisions of paragraph 5.3-5.6 of the Procurement Regulations. The other national procurement arrangements (other than national open competitive procurement), that may be applied by the Borrower shall be required to be consistent with the requirements set out in paragraphs 5.3 and 5.4 d as appropriate of the Procurement Regulations.

48. **Institutional Arrangements for Procurement:** The MoH will be the implementing agency responsible for procurement activities at the national level, while KEMSA will be responsible for procurement and distribution of HPTs to primary care facilities. Counties will also conduct procurement on a need-by-need basis under Sub-components 2.2 and 2.3, based on their AWPs. All entities have gained significant experience in implementing World Bank-financed projects.
The MoH and the 47 counties implemented a Bank-financed THS-UCP using Procurement Guidelines in the period 20162023. Furthermore, the MoH and KEMSA have been implementing the World Bank-financed COVID-19 Health Emergency Response Project (CHERP, P173820) since 2020 using Procurement Regulations. Implementation of these Bank-financed operations have enhanced and continue to strengthen the agencies’ institutional procurement capacities in implementing Page 21 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems(P179698)

**VII.** **RESULTS FRAMEWORK AND MONITORING**

@#&OPS~Doctype~OPS^dynamics@padannexresultframework#doctemplate

**PDO Indicators by PDO Outcomes**

Baseline Period 1 Closing Period
**Improve utilization of quality primary health care services**
**Percentage of women receiving postnatal care within 48 hours (Percentage)**
Oct/2023 Jun/2027 Jun/2029 57.3 61 65 Percentage of women receiving postnatal care within 48 hours in the 10 selected counties (Percentage) 56.6 60 65 Percentage of host community women receiving postnatal care within 48 hours in Garissa and Turkana (Percentage) 57.3 61 65 Percentage of refugee women receiving postnatal care within 48 hours in Garissa and Turkana (Percentage) 83.5 84.5 86
**Percentage of children immunized with three doses of Pentavalent vaccine (Percentage)**
Oct/2023 Jun/2027 Jun/2029 77.2 81 85 Percentage of children immunized with three doses of the Pentavalent vaccine in the 10 selected counties (Percentage) 76 79 82
**To improve quality of primary health care services**
**Percentage of pregnant women attending 4 or more ANC visits (Percentage)**
Oct/2023 Jun/2027 Jun/2029 50.1 53 56 Percentage of pregnant women attending 4 or more ANC visits in the 10 selected counties (Percentage) 42.7 46 50 Percentage of host community pregnant women attending 4 or more ANC visits in Garissa and Turkana (Percentage) 51.6 53.5 56 Percentage of refugee pregnant women attending 4 or more ANC visits in Garissa and Turkana (Percentage) 80 83 86 Feb 21, 2024 Page 26 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**Monitoring & Evaluation Plan: PDO Indicators by PDO Outcomes**

**Outcome 1: Improve utilization of quality primary health care services**
**Percentage of women receiving postnatal care within 48 hours (Percentage)**

Numerator: Number of women receiving postnatal care after delivery within 48 hours.
Description Denominator: Total number of expected live births during the reporting period Frequency Every six months Data source KHIS Methodology for Data Routine Health Management Information System (HMIS) data collection Collection Responsibility for Data MoH Collection

**Percentage of women receiving postnatal care within 48 hours in the 10 selected counties (Percentage)**

Numerator: Number of women, in the 10 selected counties, receiving postnatal care after delivery within 48 hours.
Description Denominator: Total number of expected live births, in the 10 selected counties, during the reporting period Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Percentage of host community women receiving postnatal care within 48 hours in Garissa and Turkana (Percentage)**

Numerator: Number of host community women in Garissa and Turkana, receiving postnatal care after delivery within 48 Description hours. Denominator: Total number of expected live births within the host commnunity of Garissa and Turkana, during the reporting period Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Description Responsibility for Data MoH Collection

**Percentage of refugee women receiving postnatal care within 48 hours in Garissa and Turkana (Percentage)**

Numerator: Number of refugee women in Garissa and Turkana, receiving postnatal care after delivery within 48 hours.

Description Denominator: Total number of expected live births within the refugee community in Garissa and Turkana, during the reporting period Frequency Every six months Data source UNHCR reports Methodology for Data Routine UNHCR data collection Collection Description Responsibility for Data MoH Collection

**Percentage of children immunized with three doses of Pentavalent vaccine (Percentage)**

Numerator: Number of children under 1 year who have received three doses of the Pentavalent vaccine Description Denominator: Total number of surviving children under 1 year Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Feb 21, 2024 Page 30 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) Collection
**Percentage of children immunized with three doses of Pentavalent vaccine in the 10 selected counties (Percentage)**

Numerator: Number of children under 1 year who have received three doses of the Pentavalent vaccine in the 10 Description selected counties. Denominator: Total number of surviving children under 1 year in the 10 selected counties.
Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Outcome 2: To improve quality of primary health care services**
**Percentage of pregnant women attending 4 or more ANC visits (Percentage)**

Numerator: Number of women attending 4 or more ANC visits.
Description Denominator: Total number of expected live births during the reporting period.
Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Percentage of pregnant women attending 4 or more ANC visits in the 10 selected counties (Percentage)**

Numerator: Number of women attending 4 or more ANC visits in the 10 selected counties.
Description Denominator: Total number of expected live births during the reporting period in the 10 selected counties.
Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Percentage of host community pregnant women attending 4 or more ANC visits in Garissa and Turkana (Percentage)**

Numerator: Number of pregnant women within the host cummunity of Garissa and Turkana attending 4 or more ANC Description visits. Denominator: Total number of expected live births during the reporting period within the host community of Garissa and Turkana Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Description Responsibility for Data MoH Collection

**Percentage of refugee pregnant women attending 4 or more ANC visits in Garissa and Turkana (Percentage)**

Numerator: Number of refugee pregnant women attending 4 or more ANC visits.

Description Denominator: Total number of expected live births during the reporting period within the refugee community of Garissa and Turkana Frequency Every six months Data source UNHCR reports Methodology for Data Routine UNHCR data collection Collection Responsibility for Data MoH Collection

**Proportion of Children Under 5 with diarrhea treated with Zinc/ORS Co-Pack (Percentage)**

Feb 21, 2024 Page 31 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) Numerator: Total number of children receiving Zinc/ORS co-pack Description Denominator: Total number of children under 5 years with diarrhea Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Proportion of Children Under 5 with diarrhea treated with Zinc/ORS Co-Pack in the 10 selected counties (Percentage)**

Numerator: Total number of children receiving Zinc/ORS co-pack in the 10 selected counties.
Description Denominator: Total number of children under 5 years with diarrhea in the 10 selected counties.
Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Outcome 3: To strengthen institutional capacity for service delivery**
**Order fill rate for priority health products and technologies (HPTs) (Percentage)**
Description Percentage of orders fulfilled as per agreed requirements for priority health products and technologies (HPTs).
Frequency Every six months Data source ERP Methodology for Data Routine ERP data Collection Responsibility for Data KEMSA, MoH Collection

**Order turnaround time (Days)**

Average number of days taken to process and deliver to the last mile, priority health products and technologies (HPTs) Description orders from the date the order is placed.
Frequency Every six months Data source ERP Methodology for Data Routine ERP data Collection Responsibility for Data KEMSA, MoH Collection

**Monitoring & Evaluation Plan: Intermediate Results Indicators by Components**

**Strengthening institutional capacity for health service delivery towards achieving UHC**
**Number of functional ERP modules (Number)**
Description Total number of functional modules in the new KEMSA ERP system.
Frequency Every six months Data source Project report Methodology for Data Project monitoring Collection Responsibility for Data KEMSA, MoH Collection

**Number of surveys completed (Number)**
Description Total number of surveys completed with support from the project.
Frequency Every six months Feb 21, 2024 Page 32 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) Description Total number of deliveries attended by skilled health personnel Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Number of community enrolled health nurses trained in Garissa and Turkana (Number)**
Description Total number of community enrolled health nurses trained in Garissa and Turkana Frequency Every six months Data source Project report Methodology for Data Project monitoring Collection Responsibility for Data MoH Collection

**Number of refugee health facilities supported under the project, as part of the transition to county management, in Garissa and Turkana**
**(Number)**

Total number of refugee health facilities supported under the project, as part of the transition to county management, in Description Garissa and Turkana (registration in the master facility list, provision of non-program HPTs from KEMSA, staffing).
Frequency Every six months Data source Project report Methodology for Data Project monitoring Collection Responsibility for Data MoH Collection

**People in Garissa and Turkana who have received essential health, nutrition, and population (HNP) services (Number)**

Total number of deliveries attended by skilled health personnel and total number of children immunized among the host Description community and refugees in Garissa and Turkana.
Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Number of children immunized among the host community in Garissa and Turkana (Number)**
Description Total number of children immunized among the host community in Garissa and Turkana.
Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Number of children immunized among refugees in Garissa and Turkana (Number)**
Description Total number of children immunized among refugees in Garissa and Turkana.
Frequency Every six months Data source UNHCR reports Methodology for Data Routine UNHCR data collection Collection Responsibility for Data MoH Collection Feb 21, 2024 Page 34 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**Number of deliveries attended by skilled health personnel among the host community in Garissa and Turkana (Number)**
Description Total number of deliveries attended by skilled health personnel among the host community in Garissa and Turkana.
Frequency Every six months Data source KHIS Methodology for Data Routine HMIS data collection Collection Responsibility for Data MoH Collection

**Number of deliveries attended by skilled health personnel among refugees in Garissa and Turkana (Number)**
Description Total number of deliveries attended by skilled health personnel among the refugees in Garissa and Turkana Frequency Every six months Data source UNHCR reports Methodology for Data Routine UNHCR data collection Collection Responsibility for Data PMT Collection

**Project management and evaluation**
**Percentage of complaints in the GRM satisfactorily addressed within 4 weeks of initial complaint being recorded (Percentage)**

Numerator: Number of complaints to the GRM satisfactorily addressed within 4 weeks of initial complaint being Description recorded. Denominator: Total number of recorded complaints to the GRM.
Frequency Every 6 months Data source Project report Methodology for Data Project monitoring Collection Responsibility for Data MoH Collection

**A vulnerable and marginalized group plan is developed and disseminated (Yes/No)**
Description A vulnerable and marginalized group plan is developed and disseminated Frequency Every six months Data source Project report Methodology for Data Project monitoring Collection Responsibility for Data MoH Collection

**Percentage of transfers of project funds to the CRF that occur within 7 business days after the project funds are transferred into the MoH**
**Development Account**

Numerator: Number of transfers of project funds to the CRF that occur within 7 business days after the project funds are transferred into the MoH Development Account Description Denominator: Total number of transfers of project funds to the CRF that occur after the project funds are transferred into the MoH Development Account in a given year Frequency Every six months Data source Project report Methodology for Data Project monitoring Collection Description Responsibility for Data MoH Collection Feb 21, 2024 Page 35 of 43


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**ANNEX 1: Implementation Arrangements and Support Plan**

**COUNTRY: Republic of Kenya**
**Building Resilient and Responsive Health Systems**

**Project institutional and implementation arrangements**

1. **The implementation support plan for the project is based on the following considerations:** (a) for Component
2, the annual planning, budgeting, implementation, and monitoring will follow county public financial management (PFM) process and county Governments will be responsible for implementation with support from KEMSA for procurement and delivery of HPTs to primary care facilities; (b) all activities under Component 1 will be implemented by the MoH and KEMSA as part of their work program; (c) all implementing entities will put in place a management team to oversee project implementation; (d) in refugee camps, implementation will be undertaken in close coordination with DRS and UNHCR; and (e) the PMT will coordinate both the county and national level activities.

**Financial Management**

2. **Planning and Budgeting** . The project budgeting will be done in accordance with existing Government procedures.
The budget shall be based on the Annual Work Plan and Budget (AWPB) developed by the MoH including activities to be carried out by Counties and KEMSA. The project planning and budgetary process shall be implemented in accordance with the standard Government fiscal year which begins on 1st July of each financial year as provided for by the Public Financial Management Act 2012 and the Government Financial Regulations and Procedures. These will form the basis for defining the project activities and ensuring that sufficient funds are allocated to achieve the agreed results. There are possible challenges on inadequate budget allocations in the printed estimates at MoH which may delay implementation of project activities. Coordination timing of the Government budgeting activities/calendar across the two project levels (National and County) may be a challenge. The Chief Finance Officer at MoH will be tasked to liaise with the PMT to ensure there is adequate budget provided **.** 3. **Accounting and Staffing.** All implementing entities including the participating counties will be required to designate project finance staff with adequate qualifications and experience to ensure project financial processes are well coordinated, including preparations of financial reports for the project. The proposed staff will be reviewed and cleared by the World Bank as an effectiveness condition. The MoH maintains projects’ books of account using the integrated financial management information system (IFMIS) and manual ledgers. There will be comprehensive start-up workshop where finance staff of the implementing entities will be sensitized on FM requirements for the project to build capacity on managing the project. Additional training will be provided on a need basis during project implementation.

4. **Internal Control and Internal Audit.** The project expenditure initiation, authorization and payments will be in line with PFM Act 2012 and PFM regulations (2015) of Kenya as elaborated and customized in the FM manual. Project work plans will be integrated into the internal audit work plans. Internal Audit reports covering project activities will be shared with the World Bank on a semi-annual basis (i.e. 30 June and 31 December). Regular internal audit, implementation support, monitoring and reporting will be undertaken. There have been material weaknesses on imprest management at MoH regarding long outstanding imprest and multiple imprest contravening PFM regulations. The internal audit at MoH Feb 21, 2024 Page 36 of 43

integrated financial management information system


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698)

**ANNEX 2: Climate Change**
1. **The project has been screened for climate disasters and risks and been found to be highly exposed, while the**
**risk to project activities is low.** Kenya is highly vulnerable to the impacts of climate change and is ranked 152 out of 181
countries in the 2019 Notre Dame Global Adaptation Index (ND-GAIN). Kenya’s topography is highly diverse including varied formations of plains, escarpments, and hills, as well as low and high mountains which has an influence on varying climatology and related climate vulnerability across the country. Kenya’s mean annual temperature is 24.3°C, with average monthly temperatures between 22°C in the coolest months (July/August) and 25.6°C in the warmest months (February/March). The mean annual temperature across Kenya is projected to increase by 1.0°C in the 2030s, 1.7°C in the mid-century and 3.5°C by the end of the century, with rapid warming in the northern and coastal parts of the country, intensifying droughts, heat waves with impacts on heat health risks, and food insecurity and malnutrition. The mean annual precipitation (1901-2020) is 668.6mm and is projected to remain highly variable and uncertain, with an increase in average rainfall in the 2050s with increased extreme rainfall events (frequency, intensity, duration) triggering floods and landslides with implications for vector-borne disease transmission, water-borne disease outbreaks, direct injuries, and mortalities; and impacts on health infrastructure. Floods and droughts are the most significant and frequent climaterelated hazards accounting for 40.0 percent and 10.0 percent respectively of all-natural hazard occurrences in Kenya between 1980-2020.

2. **Climate change has significant impacts on health in Kenya** . Food insecurity and malnutrition remain high particularly in the Arid and Semi-Arid Lands of Kenya. Increased precipitation variability and related prolonged droughts and erratic rainfall induced floods are posing significant impacts on food security, driving hunger and malnutrition in the country and projected increases in temperature and decrease in precipitation will worsen food insecurity and associated malnutrition in the country by the 2030s and 2050s. Three consecutive years of below than average rains, prolonged drought and erratic rains have significantly reduced crop yields and livestock productivity leaving 17.0 percent (2.8 million people) facing acute food insecurity, and 940,000 children 6-59 months and 145,000 pregnant or lactating women acutely malnourished. [29] Furthermore, warming temperatures and precipitation variability are already increasing vector-borne disease transmission risk (especially for malaria, dengue, schistosomiasis, chikungunya, yellow fever, rift valley fever) in the country. For instance, in Kenya, malaria is a major cause of death and disease with an estimated 3.5 million cases and 10,700 deaths each year; with 31 million people at risk in the endemic Lake Western, Nyanza and Coastal regions. [30] [31] Projected increasing temperatures and rainfall variability are predicted to increase habitat suitability and seasonal transmission in traditionally low malaria risk areas such as the Central highlands and Nairobi. Women, children, and pregnant mothers, particularly those from poor households and in rural areas are the most vulnerable to malaria. Climate change is also exacerbating water-borne diseases especially diarrhea and cholera outbreaks in Kenya. Flash floods are overwhelming sewage systems contaminating drinking water sources and prolonged droughts are reducing the quantity and quality of water and compromising the functioning of Water, Sanitation, and Hygiene infrastructure even in health facilities. In the aftermath of heavy rains during March-May 2018, flooding across the country led to a major increase in cholera outbreaks of 5,470 cases and 78 deaths in 19 counties with over 700 cases in Turkana and Garissa Counties. [32] [33] Floods, storms, landslides, and extreme heat threaten the functioning of health infrastructure and hinder health service delivery and access especially in flood prone Coastal regions, Tana River region, the Lake Victoria Basin, and rural remote areas of the country.

29 Kenya: IPC Acute Food Insecurity and Acute Malnutrition Analysis (July 2023 - January 2024) 30 https://www.cdc.gov/malaria/malaria_worldwide/cdc_activities/kenya.html 31 Kenya Malaria Indicator Survey, 2020.
32 Kenya Humanitarian Situation Report. 31 December 2018.
33 MSF responds to cholera outbreak amid heavy rains and flooding. Project update. 18 May 2018.

Feb 21, 2024 Page 40 of 43

IPC Acute Food Insecurity and Acute Malnutrition Analysis


Input:
**The World Bank**
Building Resilient and Responsive Health Systems (P179698) 3. The project intends to implement measures to adapt to climate change while mitigating greenhouse gas emissions, as outlined in the Table below.

**Table 1: Climate Adaptation Measures Financed by the Project**

**Components/Sub-component** **Climate Action**

Sub-component 1.1: Institutional and operational reforms to enhance efficiency and transparency of KEMSA (US$30 million) Sub-component 1.3: Improve availability of quality data for decision making (US$10 million) Sub-component 2.1: Improving availability of essential HPTs and delivery of key RMNCAH and NCDs interventions at the primary care level (US$90 million): Sub-component 2.3: Improving access to and utilization of quality health services in refugee and host communities (US$40 million)

**HPTs for Climate Sensitive diseases:** The list of selected HPTs will include
those related to climate sensitive diseases and conditions (malaria, diarrheal diseases, etc.). Availability of HPTs for climate related diseases will lead to enhanced and continued quality health service delivery for poor and rural populations even during extreme events (floods, heat waves). **(adaptation)**

**Climate measures in surveys:** To improve decision making and planning for
climate sensitive diseases and conditions, and climate impacts on health infrastructure and health service delivery, there is need for availability of reliable health data. Therefore, questions on climate and health impacts will be included in the survey. **(adaptation)**

**HPTs for Climate Sensitive diseases** : Pharmaceuticals for climate sensitive
conditions such as malaria, diarrheal diseases, and other climate sensitive conditions will be included in the pharmaceutical list. This will improve the capacity of primary care level facilities to provide better health services in the face of the increasing burden of disease due to climate change. Seasonal case and pharmaceutical consumption data will be used to inform procurement of the pharmaceuticals to ensure adequate supplies based on seasonal patterns to address climate sensitive conditions. **(adaptation)**

**Climate sensitive community health service planning:** Climate sensitive
planning including the use of climate vulnerability and meteorologic data will be used to guide the distribution of essential HTPs, diagnostic and medical equipment avoiding stormy, heavy rains and heavy flooding days.
Specifically, data on climate vulnerable locations and data on previous use of HPTs for climate sensitive diseases as well as patterns of pharmaceutical use following climate shocks will be used to ensure adequate quantities of pharmaceuticals are being used. To ensure pharmaceuticals are available ahead of shocks and that these do not impact distribution, funding will be made available, and planning will be done to ensure distributions ahead of shocks. This will reduce the risk of damage to HPTs and medical equipment by floods and storms but will also improve the acquisition and availability of adequate amounts of essential HPTs (for climate sensitive diseases such as malaria, diarrhea) for improved health service delivery. **(adaptation)**

**Availability of climate sensitive essential HPTs, diagnostic and medical**
**equipment:** This Sub-component will finance the procurement of HPTs for
climate sensitive diseases, particularly malaria and diarrhea, which are Feb 21, 2024 Page 41 of 43

Seasonal case and pharmaceutical consumption data

climate vulnerability and meteorologic data


Input:
ABBREVIATIONS AND ACRONYMS

|ANC|Antenatal Care|
|---|---|
|BEmONC|Basic Emergency Obstetric and Newborn Care|
|BHI|Boma Health Initiative|
|BHW|Boma Health Worker|
|BHT|Boma Health Team|
|BPHNS|Basic Package of Health and Nutrition Services|
|CEmONC|Comprehensive Emergency Obstetric and Newborn Care|
|CEN|Country Engagement Note|
|CERC|Contingent Emergency Response Component|
|CMR|Clinical Management of Rape|
|COVID-19|Coronavirus Disease 2019|
|CRA|Commission for Refugee Affairs|
|DHIS2|District Health Information Software 2|
|ESF|Environmental and Social Framework|
|ESMAP|Energy Sector Management Assistance Program|
|ESMF|Environmental and Social Management Framework|
|EU|European Union|
|FCDO|Foreign, Commonwealth and Development Office|
|FCV|Fragility, Conflict and Violence|
|FM|Financial Management|
|Gavi|Gavi, the Vaccine Alliance|
|GBV|Gender-based Violence|
|GCP|Global Challenges Program|
|GDP|Gross Domestic Product|
|GEMS|Geo-Enabling for Monitoring and Supervision|
|GRM|Grievance Redress Mechanism|
|HCI|Human Capital Index|
|HEIS|Hands-on Extended Implementation Support|
|HMIS|Health Management Information System|
|HNP|Health, Nutrition, and Population|
|HPF|Health Pooled Fund|
|HRH|Human Resources for Health|
|HSC|High-Level Steering Committee|
|HSF|Health Service Functionality|
|HSSP|Health Sector Strategic Plan|
|HSTP|Health Sector Transformation Project|
|ICRC|International Committee of the Red Cross|
|IDP|Internally Displaced People|
|IDSR|Integrated Disease Surveillance and Response|
|IEC|Information. Education, and Communication|
|IMF|International Monetary Fund|
|IMNCI|Integrated Management of Neonatal and Childhood Illness|
|IP|Implementing Partner|
|IPC|Integrated Food Security Phase Classification|
|IPF|Investment Project Financing|


Input:
**The World Bank**
South Sudan Health Sector Transformation Project (HSTP) (P181385)

|E & S Standards|Relevance|
|---|---|
|ESS 1: Assessment and Management of Environmental and Social Risks and
Impacts|Relevant|
|ESS 10: Stakeholder Engagement and Information Disclosure|Relevant|
|ESS 2: Labor and Working Conditions|Relevant|
|ESS 3: Resource Efficiency and Pollution Prevention and Management|Relevant|
|ESS 4: Community Health and Safety|Relevant|
|ESS 5: Land Acquisition, Restrictions on Land Use and Involuntary Resettlement|Relevant|
|ESS 6: Biodiversity Conservation and Sustainable Management of Living Natural
Resources|Relevant|

Page 5 of 68


Input:
**The World Bank**
South Sudan Health Sector Transformation Project (HSTP) (P181385)

|ESS 7: Indigenous Peoples/Sub-Saharan African Historically Underserved<br>Traditional Local Communities|Relevant|
|---|---|
|ESS 8: Cultural Heritage|Relevant|
|ESS 9: Financial Intermediaries|Not Currently Relevant|

Page 6 of 68


Input:
**The World Bank**
South Sudan Health Sector Transformation Project (HSTP) (P181385)

|Type|Citation|Description|Financing Source|
|---|---|---|---|
|Effectiveness|Article V, 5.01.(a)|The MDTF Agreement has
been executed and
delivered and all conditions
precedent to its
effectiveness or to the right
of the Recipient to make
withdrawals under it (other
than the effectiveness of
this Agreement) have been
fulfilled.|IBRD/IDA|
|Effectiveness|Article V, 5.01.(b)|The Association is satisfied
that the Recipient has an
adequate refugee
protection framework.|IBRD/IDA|
|Effectiveness|Article V, 5.01.(c)|The Recipient has
established the Project
Management Unit in
accordance with the
provisions of Section I.A.3
of Schedule 2 to this
Agreement and recruited
its key staff, namely (i) a
Project Manager, (ii) a
financial management
specialist, and a (iii) a|IBRD/IDA|

Page 7 of 68


Input:
**The World Bank**
South Sudan Health Sector Transformation Project (HSTP) (P181385)

**I.** **STRATEGIC CONTEXT**

**A. Country Context**

1. **The history of South Sudan has been marked with bouts of conflict and efforts for peace and stability.** After

prolonged armed conflict with northern Sudan and the Comprehensive Peace Agreement in 2005, the Republic of
South Sudan emerged as the world’s youngest country in 2011. In 2013, a civil war erupted in the nascent country,
which ended with the signing of the Revitalized Agreement on the Resolution of the Conflict in the Republic of
South Sudan (R-ARCSS). As a result of consecutive wars, the country has experienced only about 15 years of peace
since 1955, specifically during 1972–1982 and 2005–2011. While a series of encouraging reforms have been
undertaken to support longer-term stability and development outcomes, the country continues to struggle with
the lingering impact of prolonged conflict, including widespread levels of poverty, elevated violence in several
areas, weakened institutions, untapped human capital, lack of access to basic services, food insecurity, and a nondiversified economy.

2. **South Sudan is one of the poorest countries in the world with over 80 percent of people living in poverty.** South


Input:
Sudan’s GDP is estimated to have contracted by 0.4 percent in FY 2022/23, [1] weighed down by a fourth consecutive
year of flooding, lingering impacts of the COVID-19 pandemic, violence flareups, and higher food inflation due to
global crises. [3] The 2022 Household Budget Survey estimates that poverty levels in South Sudan remain persistently
high–at around 80 percent of the population, with 6 in 10 South Sudanese living in extreme poverty (below the
food poverty line). Nearly 80 percent of South Sudan’s population lives in rural areas where infrastructure is
limited, complicating service delivery, particularly during the rainy season.

3. **South Sudan has the highest level of vulnerability and lowest level of climate adaptation capacity globally**, based


Input:
1World Bank. Macro Poverty Indicator, October 2023.
2 Inform Risk Index, 2024: https://www.worldbank.org/en/news/immersive-story/2023/04/25/water-security-and-fragility-insights-from-southsudan; and World Bank, Global Water Security and Sanitation Partnership, Rising from the Depths: Water Security and Fragility in South Sudan; May
2023. https://www.worldbank.org/en/news/immersive-story/2023/04/25/water-security-and-fragility-insights-from-south-sudan.
3 The country is composed of the Bahr el Ghazal, Bahr el Jebel, and Baro-Akobo-Sobat River Basins, which converge into a fourth, the Upper Nile
River basin, which lace the country with a network of rivers and tributaries that flood annually. World Bank, Global Water Security and Sanitation
Partnership, Rising from the Depths: Water Security and Fragility in South Sudan; May 2023. https://www.worldbank.org/en/news/immersivestory/2023/04/25/water-security-and-fragility-insights-from-south-sudan.

Macro Poverty Indicator
Inform Risk Index, 2024


Input:
**education, and food rations in refugee camps administered by UNHCR than members of host communities**, who
tend to live in isolated areas where government services and market-based opportunities are either highly limited
or non-existent. For this reason, UNHCR makes specific efforts to support host communities, to the extent that
resources allow. The onset of the crisis in Sudan and the large number of arrivals in northern border areas have
further exacerbated the need for resources addressing interventions around forced displacement in the country.
With most of the humanitarian agencies scaling down their support in the country, the project will need to play a
more significant role to fill the gap.

8. **The Government of South Sudan has maintained an open-door policy and reaffirmed its commitment to address**