Despite substantial recent declines, general population HIV incidence in sub-Saharan Africa remains above international targets. Better description of risk factors for new infections would improve prioritisation of interventions. Using data from population-based cohorts in Kenya, Malawi, Tanzania, South Africa, Uganda, Zimbabwe we described the prevalence of risk factors for men and women aged 15-24 and 25-49 and estimated the association between individual and community-level risk factors and HIV acquisition between 2005 and 2016. Among 43,434 men and 55,919 women aged 15 to 49 there were 4,612 seroconversions. Education, marital status, male circumcision, new sexual partners, types of partner, prevalence of untreated HIV infection in the community and community partner acquisition rates were associated with HIV incidence. Only the prevalence of untreated HIV was a risk for both sexes and apparent at all ages. The prevalence of risk factors varied by age, sex and study. HIV incidence was higher in people aged 25-49 living in communities where men had high partner acquisition rates. Our results show potential for improved prevention through changed timing of prevention interventions relative to behaviour and the utility of using community characteristics to target prevention.

Adolescent girls in Kenya face sexual and reproductive health (SRH) risks. Being in school is recognized as protecting girls from such risks, leaving out-of-school girls vulnerable to such harms but ignored in research studies. This qualitative study aimed to explore the realities of out-of-school girls in Siaya County, Kenya, with a focus on SRH risks using four transect walks with 25 participants. Thematic analysis was used to explore the data. Themes included limited contraceptive knowledge, fear of negotiating contraception, early and unintended pregnancy, unsafe abortion and exposure to HIV. Transactional sex was normalized to meet basic needs, and girls were coerced into sexual relationships, physically and verbally abused, with little agency or control over their lives. Conversely, a minority expressed sexual desire, curiosity and contraceptive choice. Being out-of-school intensifies SRH challenges and may expose girls to distinctive negative effects.

Introduction Climate change and HIV are interconnected epidemics that increase vulnerability in people living with HIV (PLWH), particularly in sub-Saharan Africa. Despite their public health significance, research on the synergistic effects of these epidemics on the health of PLWH is limited. The advancement of non-invasive wearable technology offers an opportunity to leverage objective health data for large-scale research, addressing this knowledge gap. This study will examine the impact of weather events on distinct health variables of PLWH within the Siaya Health and Demographic Surveillance System (HDSS) in rural Kenya. Methods and analysis Over a period of 6 months, we continuously monitored health parameters of a total of 200 participants including heart rate, activity and sleep, using consumer-grade wearable devices. We will correlate these health data with real-time weather parameters (ambient temperature, wet bulb globe temperature, precipitation level) from five weather stations within the HDSS area and compare between HIV-positive participants and an HIV-negative control group. Additionally, a convergent mixed-methods approach will explore participants’ perceptions of the impact of weather events on their health and personal experiences. The study aims to inform future research on the complex relationship between HIV and weather events, which are projected to increase in frequency in this region due to climate change and provide valuable insights for policymakers to develop effective measures to protect this vulnerable population amid the growing climate crisis. Ethics and dissemination This study has been approved by the Research Ethics Committees at Kenya Medical Research Institute, Nairobi (approved on 23 October 2023; SERU 4826) and Heidelberg University Hospital, Germany (approved on 14 February 2023; S-824/2022). Written informed consent was obtained from all participants prior to enrolment, with data anonymised and handled according to Kenyan and German data protection regulations. Research findings will be disseminated through peer-reviewed publications and presented at scientific conferences.

Data collection commenced under the auspices of a collaborative global health partnership by the Child Health and Mortality Prevention Surveillance (CHAMPS) network to investigate the impact of the COVID-19 pandemic and related lockdowns on child and maternal health, economic hardships, and access to care for children and pregnant women. Survey data were collected between January and August 2022 within a Health and Demographic Surveillance System (HDSS) in Western Kenya. The data were gathered using a survey instrument designed to measure household knowledge and awareness of COVID-19, experiences of economic and social hardships, changes in food availability, and challenges to accessing healthcare during the pandemic. The data are drawn from two communities in Western Kenya, one rural (Karemo) and one urban (Manyatta) and consist of a survey of 28,677 households.

Despite global commitments to girls’ education, many dropout prematurely facing health, social, and economic hardships. Using ten focus group discussions and ten in-depth interviews, this study explored issues identified as important in the lives of girls who had dropped out of school. Thematic analysis first revealed rejection as a central theme in the girls' experiences, prompting a deductive approach that identified five interrelated themes: (a) perpetrators, (b) school dropout, (c) pregnancy, (d) illness and disease, and (e) consequences. School dropout and pregnancy were key events perpetuating further rejection. These findings highlight the urgent need for targeted interventions including addressing the drivers of school dropout and adolescent pregnancy. Moreover, interventions are needed to challenge and change negative societal views. Rather than being overlooked, these girls require focused support and care to improve their well-being and life chances.

In the absence of complete civil registration and vital statistics, Health and Demographic Surveillance Systems (HDSSs) are important sources of population-based data throughout sub-Saharan Africa. However, HDSS data on the vital status of newborns are often unreliable due to omission of those who were born and died between two rounds of data collection and are therefore never enumerated. This study investigates whether pregnancy registration improves estimation of under-five mortality (U5M) in three HDSSs in The Gambia, Kenya, and South Africa. We find that mortality is higher for children whose mother's pregnancy was observed than for children who were first registered after birth. Cox proportional hazards models with inverse probability weights further suggest that this difference is probably due to improved ascertainment of deaths in pregnancy cohorts and unlikely to be driven by a selection effect. These results highlight the importance of pregnancy registration in HDSSs for the estimation of U5M.

Introduction Out-of-school girls are at higher risk of sexual and reproductive health (SRH) harms. Schools provide a protective environment for adolescents and lessen their exposure to such risks. This paper explores factors associated with school dropout, sexual activity, marriage and pregnancy among out-of-school girls in western Kenya.Methods Eligible adolescents were systematically recruited from area households in Siaya County. Generalised linear models were fit to obtain adjusted ORs (aOR) and 95% CIs of key covariates against individual outcomes. Factors with p values <0.1 in the univariate analysis were added to a multivariable model using backward stepwise regression techniques, and factors significant at p<0.05 were retained in the final adjusted models. Models were bootstrapped at 1000 replications to validate factor selection.Results Of the 915 girls enrolled (mean 18.3 years, SD: 1.3), 2.1% had never attended school. Of those who started school, 34.6% dropped out during primary education. Reasons for dropout included marriage, pregnancy and needing childcare (42.5%), financial reasons (eg, lack of school fees, needing to work, 42.5%), lack of interest (5.6%), illness (3.0%), failing school (2.2%) and other factors (4.1%). Reaching menarche prior to age 13 (aOR 1.50, 95% CI 1.00 to 2.23, p=0.048), experiencing physical violence (aOR 1.48, 95% CI 1.01 to 2.17, p=0.042) or sexual partner violence (aOR 2.16, 95% CI 1.08 to 4.34, p=0.030) were associated with not completing primary school. Experiencing sexual harassment (aOR 2.20, 95% CI 1.35 to 3.58, p=0.002) or needing to engage in transactional sex (aOR 1.74, 95% CI 1.20 to 2.51, p=0.003) were associated with being sexually active. Low socioeconomic status (aOR 1.98, 95% CI 1.36 to 2.90, p<0.001), having an older partner (aOR 1.65, 95% CI 1.10 to 2.47, p=0.016) and higher parity (aOR 2.56, 95% CI 1.42 to 4.62, p=0.002) were associated with being married or cohabiting with a partner. Girls identified provision of school fees and schooling items (67.9%) as the primary solution to resuming school; obtaining counselling, mentorship and support services (22.2%) for their general health; and provision of menstrual products (24.2%) for daily challenges.Conclusions Out-of-school girls in western Kenya face numerous SRH challenges related to menstruation, sexual and physical violence, and poverty. Social and financial support and interventions for school re-entry are warranted for this neglected population. National policies and multisectoral strategies to support adolescent girls’ education and health should be prioritised, enforced and monitored for impact.

BACKGROUND:Many adolescent girls drop out of school in sub-Saharan Africa. Mental health problems in this population and their risk factors are a neglected research area. METHODS:This community-based cross-sectional survey studied 904 out-of-school girls in rural western Kenya. Outcome variables were a positive screen for anxiety (GAD-7), depression (PHQ-A), post-traumatic stress disorder (PTSD; PCL-C), and a composite measure for overall symptom severity. Survey data were analysed with univariable and multivariable binary logistic and multiple linear regression analyses using SPSS 29.0. FINDINGS:The prevalence of probable anxiety was 10.6%, of probable depression 15.9%, and of probable PTSD 18.0%. One of the three items on suicidal ideation or past suicide attempt was reported by 40.2% of girls. In multivariable analyses controlling for age, fear of sexual assault and functional limitations due to menstruation were uniquely associated with each of the outcome variables, and exposure to physical violence to each outcome except anxiety. Other risk factors showed a less consistent relationship with outcome. The cross-sectional study design precludes any temporal and causal inference for the reported significant associations. CONCLUSION:Out-of-school girls constitute a vulnerable group with high levels of PTSD and suicide risk. Multi-level and multi-sector interventions are needed to help these girls cope with their mental health problems and to address mutable risk factors such as gender-based partner and non-partner sexual and physical violence, poor menstrual hygiene, and poverty.

The impact of the COVID-19 pandemic on pediatric mortality, including measures to ensure continuity of HIV care, is not well described in Kenya. We evaluated causes of death (COD) among decedents under 5 years of age both before and during the COVID-19 pandemic in Kenya. We analyzed Child Health and Mortality Prevention Surveillance (CHAMPS) data collected in February 2018–March 2022. We describe the proportional contribution of specific conditions in the causal chain of death among decedents aged 28 days to 59 months who underwent minimally invasive tissue (MITS) sampling, had an HIV polymerase chain reaction, and a COD determination. We also calculated all-cause and HIV cause-specific mortality rates using data from two health and demographic surveillance system (HDSS) sites in western Kenya. Results were stratified by time periods: February 2018 to February 2020, and March 2020 to March 2022. Among 269 MITS-eligible decedents, 55.8% died during the pre-COVID period. Of these, 53.7% were infants (28 days to 11 months), and 9.7% were HIV-positive. Leading causes of death for infants included malnutrition (20.5%), pneumonia (17.5%), sepsis (17.1%), and malaria (14.5%). For older children (12–59 months), the predominant causes were malaria (25.6%), malnutrition (21.1%), pneumonia (14.1%), and sepsis (13.1%). All-cause mortality rates did not differ significantly between the periods (53.9 vs. 52.8 per 1,000 live births, p=0.77), but HIV cause-specific mortality rates were significantly lower during March 2020–March 2022 compared to February 2018–February 2020 (1.2 vs. 3.1 per 1,000 live births, p=0.01). Malaria, malnutrition, pneumonia, and sepsis were the leading COD among decedents aged 28 days to 59 months enrolled in CHAMPS between February 2018 and March 2022. These findings may point to the need for urgent, focused efforts to prevent avoidable child deaths. Continued monitoring of HIV-related mortality could provide insights into the ongoing impact of the HIV program in the region.

Rising temperatures in Africa present an increasing threat to agricultural productivity and public health, particularly among subsistence farming communities reliant on rain-fed agriculture. Heat exposure can impair farmers’ work capacity, disrupt harvests, and heighten health risks, especially for young children vulnerable to undernutrition. The Heat to Harvest (H2H) study investigates how environmental heat exposure influences farmers’ physiological and behavioral responses, and how these in turn affect harvest yields and child nutrition. It also examines differences in labor performance and recovery between households with and without cool roof coatings, although this intervention is not the central focus. H2H is designed as a prospective cohort study nested within two Health and Demographic Surveillance Systems (HDSS) in Nouna, Burkina Faso, and Siaya, Kenya. The study integrates environmental monitoring (temperature and humidity sensors used to compute Wet Bulb Globe Temperature), biometric data (via wearables tracking heart rate, temperature, physical activity, energy expenditure, and sleep), and GPS tracking (capturing spatial mobility and labor duration). The study is embedded within a larger cluster-randomized controlled trial, facilitating comparative analysis under varying thermal conditions. Findings will provide evidence-based insights into how climate-related heat stress affects health and agricultural outcomes, supporting the development of targeted adaptation strategies to enhance resilience, health, and food security in vulnerable farming communities.

Background Climate change increasingly impacts health, particularly of rural populations in sub-Saharan Africa due to their limited resources for adaptation. Understanding these impacts remains a challenge, as continuous monitoring of vital signs in such populations is limited. Wearable devices (wearables) present a viable approach to studying these impacts on human health in real time. Objective The aim of this study was to assess the feasibility and effectiveness of consumer-grade wearables in measuring the health impacts of weather exposure on physiological responses (including activity, heart rate, body shell temperature, and sleep) of rural populations in western Kenya and to identify the health impacts associated with the weather exposures. Methods We conducted an observational case study in western Kenya by utilizing wearables over a 3-week period to continuously monitor various health metrics such as step count, sleep patterns, heart rate, and body shell temperature. Additionally, a local weather station provided detailed data on environmental conditions such as rainfall and heat, with measurements taken every 15 minutes. Results Our cohort comprised 83 participants (42 women and 41 men), with an average age of 33 years. We observed a positive correlation between step count and maximum wet bulb globe temperature (estimate 0.06, SE 0.02; P=.008). Although there was a negative correlation between minimum nighttime temperatures and heat index with sleep duration, these were not statistically significant. No significant correlations were found in other applied models. A cautionary heat index level was recorded on 194 (95.1%) of 204 days. Heavy rainfall (>20 mm/day) occurred on 16 (7.8%) out of 204 days. Despite 10 (21%) out of 47 devices failing, data completeness was high for sleep and step count (mean 82.6%, SD 21.3% and mean 86.1%, SD 18.9%, respectively), but low for heart rate (mean 7%, SD 14%), with adult women showing significantly higher data completeness for heart rate than men (2-sided t test: P=.003; Mann-Whitney U test: P=.001). Body shell temperature data achieved 36.2% (SD 24.5%) completeness. Conclusions Our study provides a nuanced understanding of the health impacts of weather exposures in rural Kenya. Our study’s application of wearables reveals a significant correlation between physical activity levels and high temperature stress, contrasting with other studies suggesting decreased activity in hotter conditions. This discrepancy invites further investigation into the unique socioenvironmental dynamics at play, particularly in sub-Saharan African contexts. Moreover, the nonsignificant trends observed in sleep disruption due to heat expose the need for localized climate change mitigation strategies, considering the vital role of sleep in health. These findings emphasize the need for context-specific research to inform policy and practice in regions susceptible to the adverse health effects of climate change.

Objective: To compare the causes of death for women who died during pregnancy and within the first 42 days postpartum with those of women who died between >42 days and within 1 year postpartum. Design: Open population cohort (Health and Demographic Surveillance Systems). Setting: Ten Health and Demographic Surveillance Systems (HDSS) in The Gambia, Kenya, Malawi, Tanzania, Ethiopia and South Africa. Population: 2114 deaths which occurred within 1 year of the end of pregnancy where a verbal autopsy interview was conducted from 2000 to 2019. Methods: InterVA5 and InSilicoVA verbal autopsy algorithms were used to attribute the most likely underlying cause of death, which were grouped according to adapted International Classification of Diseases-Maternal Mortality categories. Multinomial regression was used to compare differences in causes of deaths within 42 days versus 43-365 days postpartum adjusting for HDSS and time period (2000-2009 and 2010-2019). Main outcome measures: Cause of death and the verbal autopsy Circumstances of Mortality Categories (COMCATs). Results: Of 2114 deaths, 1212 deaths occurred within 42 days postpartum and 902 between 43 and 365 days postpartum. Compared with deaths within 42 days, deaths from HIV and TB, other infectious diseases, and non-communicable diseases constituted a significantly larger proportion of late pregnancy-related deaths beyond 42 days postpartum, and health system failures were important in the circumstances of those deaths. The contribution of HIV and TB to deaths beyond 42 days postpartum was greatest in Southern Africa. The causes of pregnancy-related mortality within and beyond 42 days postpartum did not change significantly between 2000-2009 and 2010-2019. Conclusions: Cause of death data from the extended postpartum period are critical to inform prevention. The dominance of HIV and TB, other infectious and non-communicable diseases to (late) pregnancy-related mortality highlights the need for better integration non-obstetric care with ante-, intra-and postpartum care in high-burden settings.

Background Malaria mortality is influenced by several factors including climatic and environmental factors, interventions, socioeconomic status (SES) and access to health systems. Here, we investigated the joint effects of climatic and non-climatic factors on under-five malaria mortality at different spatial scales using data from a Health and Demographic Surveillance System (HDSS) in western Kenya.Methods We fitted Bayesian spatiotemporal (zero-inflated) negative binomial models to monthly mortality data aggregated at the village scale and over the catchment areas of the health facilities within the HDSS, between 2008 and 2019. First order autoregressive temporal and conditional autoregressive spatial processes were included as random effects to account for temporal and spatial variation. Remotely sensed climatic and environmental variables, bed net use, SES, travel time to health facilities, proximity from water bodies/streams and altitude were included in the models to assess their association with malaria mortality.Results Increase in rainfall (mortality rate ratio (MRR)=1.12, 95% Bayesian credible interval (BCI): 1.04-1.20), Normalized Difference Vegetation Index (MRR=1.16, 95% BCI: 1.06-1.28), crop cover (MRR=1.17, 95% BCI: 1.11-1.24) and travel time to the hospital (MRR=1.09, 95% BCI: 1.04-1.13) were associated with increased mortality, whereas increase in bed net use (MRR=0.84, 95% BCI: 0.70-1.00), distance to the nearest streams (MRR=0.89, 95% BCI: 0.83-0.96), SES (MRR=0.95, 95% BCI: 0.91-1.00) and altitude (MRR=0.86, 95% BCI: 0.81-0.90) were associated with lower mortality. The effects of travel time and SES were no longer significant when data was aggregated at the health facility catchment level.Conclusion Despite the relatively small size of the HDSS, there was spatial variation in malaria mortality that peaked every May-June. The rapid decline in malaria mortality was associated with bed nets, and finer spatial scale analysis identified additional important variables. Time and spatially targeted control interventions may be helpful, and fine spatial scales should be considered when data are available.

IntoductionTransactional sex (TS) is common in areas of sub-Saharan Africa, motivated by reasons beyond financial support. Through this qualitative study we sought to understand the motivation driving TS among adolescent schoolgirls in rural western Kenya where rates are reportedly high. Identifying and understanding drivers within the local context is necessary for implementation of successful public health policy and programming to reduce the associated harms impacting health and wellbeing.MethodsTo understand the drivers of sexual behaviors, individual views, and socio-cultural norms, we spoke with schoolgirls, male peers, parents and teachers. The three latter groups may influence, encourage, and shape girls' views and behaviors and thus contribute to the perpetuation of cultural and societal norms.ResultsOne hundred and ninety-nine participants took part across 20 FGDs; 8 comprised of schoolgirl groups, and 4 each of schoolboy, parent or teacher groups. Through thematic analysis, poverty emerged as the key driver of TS and a normative behaviour amongst secondary school girls. Subthemes including parental influence, need for menstrual pads, pressure from boda boda drivers, peer pressure, and blame were part of a complex relationship linking poverty with TS.DiscussionWe conclude that whilst TS is perceived as inevitable, normal and acceptable it is not really a choice for many girls. Exploring ways to encourage communication between families, including around menstruation, may help enable girls to ask for help in acquiring essential items. In addition, education at a community level may shift social norms over time and decrease the prevalence of age-disparate TS among schoolgirls and older, wealthier men in the community.

Background Reliable mortality data are important for evaluating the impact of health interventions. However, data on mortality patterns among populations living in urban informal settlements are limited. Objectives To examine the mortality patterns and trends in an urban informal settlement in Kibera, Nairobi, Kenya, Methods Using data from a population-based surveillance platform we estimated overall and cause-specific mortality rates for all age groups using person-year-observation (pyo) denominators and using Poisson regression tested for trends in mortality rates over time. We compared associated mortality rates across groups using incidence rate ratios (IRR). Assignment of probable cause(s) of death was done using the InterVA-4 model. Results We registered 1134 deaths from 2009 to 2018, yielding a crude mortality rate of 4.4 (95% Confidence Interval [CI]4.2-4.7) per 1,000 pyo. Males had higher overall mortality rates than females (incidence rate ratio [IRR], 1.44; 95% CI, 1.28-1.62). The highest mortality rate was observed among children aged < 12 months (41.5 per 1,000 pyo; 95% CI 36.6-46.9). All-cause mortality rates among children < 12 months were higher than that of children aged 1-4 years (IRR, 8.5; 95% CI, 6.95-10.35). The overall mortality rate significantly declined over the period, from 6.7 per 1,000 pyo (95% CI, 5.7-7.8) in 2009 to 2.7 (95% CI, 2.0-3.4) per 1,000 pyo in 2018. The most common cause of death was acute respiratory infections (ARI)/pneumonia (18.1%). Among children < 5 years, the ARI/pneumonia deaths rate declined significantly over the study period (5.06 per 1,000 pyo in 2009 to 0.61 per 1,000 pyo in 2018; p = 0.004). Similarly, death due to pulmonary tuberculosis among persons 5 years and above significantly declined (0.98 per 1,000 pyo in 2009 to 0.25 per 1,000 pyo in 2018; p = 0.006). Conclusions Overall and some cause-specific mortality rates declined over time, representing important public health successes among this population.

Assessment of the relative impact of climate change on malaria dynamics is a complex problem. Climate is a well-known factor that plays a crucial role in driving malaria outbreaks in epidemic transmission areas. However, its influence in endemic environments with intensive malaria control interventions is not fully understood, mainly due to the scarcity of high-quality, long-term malaria data. The demographic surveillance systems in Africa offer unique platforms for quantifying the relative effects of weather variability on the burden of malaria. Here, using a process-based stochastic transmission model, we show that in the lowlands of malaria endemic western Kenya, variations in climatic factors played a key role in driving malaria incidence during 2008-2019, despite high bed net coverage and use among the population. The model captures some of the main mechanisms of human, parasite, and vector dynamics, and opens the possibility to forecast malaria in endemic regions, taking into account the interaction between future climatic conditions and intervention scenarios.

ObjectiveTo compare HIV prevalence estimates from routine programme data in antenatal care (ANC) clinics in western Kenya with HIV prevalence estimates in a general population sample in the era of universal test and treat (UTT). MethodsThe study was conducted in the area covered by the Siaya Health Demographic Surveillance System (Siaya HDSS) in western Kenya and used data from ANC clinics and the general population. ANC data (n = 1,724) were collected in 2018 from 13 clinics located within the HDSS. The general population was a random sample of women of reproductive age (15-49) who reside in the Siaya HDSS and participated in an HIV sero-prevalence survey in 2018 (n = 2,019). Total and age-specific HIV prevalence estimates were produced from both datasets and demographic decomposition methods were used to quantify the contribution of the differences in age distributions and age-specific HIV prevalence to the total HIV prevalence estimates. ResultsTotal HIV prevalence was 18.0% (95% CI 16.3-19.9%) in the ANC population compared with 18.4% (95% CI 16.8-20.2%) in the general population sample. At most ages, HIV prevalence was higher in the ANC population than in the general population. The age distribution of the ANC population was younger than that of the general population, and because HIV prevalence increases with age, this reduced the total HIV prevalence among ANC attendees relative to prevalence standardised to the general population age distribution. ConclusionIn the era of UTT, total HIV prevalence among ANC attendees and the general population were comparable, but age-specific HIV prevalence was higher in the ANC population in most age groups. The expansion of treatment may have led to changes in both the fertility of women living with HIV and their use of ANC services, and our results lend support to the assertion that the relationship between ANC and general population HIV prevalence estimates are highly dynamic.

Abstract Background Malaria deaths among children have been declining worldwide during the last two decades. Despite preventive, epidemiologic and therapy-development work, mortality rate decline has stagnated in western Kenya resulting in persistently high child malaria morbidity and mortality. The aim of this study was to identify public health determinants influencing the high burden of malaria deaths among children in this region. Methods A total of 221,929 children, 111,488 females and 110,441 males, under the age of 5 years were enrolled in the Kenya Medical Research Institute/Center for Disease Control Health and Demographic Surveillance System (KEMRI/CDC HDSS) study area in Siaya County during the period 2003–2013. Cause of death was determined by use of verbal autopsy. Age-specific mortality rates were computed, and cox proportional hazard regression was used to model time to malaria death controlling for the socio-demographic factors. A variety of demographic, social and epidemiologic factors were examined. Results In total 8,696 (3.9%) children died during the study period. Malaria was the most prevalent cause of death and constituted 33.2% of all causes of death, followed by acute respiratory infections (26.7%) and HIV/AIDS related deaths (18.6%). There was a marked decrease in overall mortality rate from 2003 to 2013, except for a spike in the rates in 2008. The hazard of death differed between age groups with the youngest having the highest hazard of death HR 6.07 (95% CI 5.10–7.22). Overall, the risk attenuated with age and mortality risks were limited beyond 4 years of age. Longer distance to healthcare HR of 1.44 (95% CI 1.29–1.60), l ow maternal education HR 3.91 (95% CI 1.86–8.22), and low socioeconomic status HR 1.44 (95% CI 1.26–1.64) were all significantly associated with increased hazard of malaria death among children. Conclusions While child mortality due to malaria in the study area in Western Kenya, has been decreasing, a final step toward significant risk reduction is yet to be accomplished. This study highlights residual proximal determinants of risk which can further inform preventive actions.

Background: Despite considerable progress made over the past 20 years in reducing the global burden of malaria, the disease remains a major public health problem and there is concern that climate change might expand suitable areas for transmission. This study investigated the relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya.Methods: Bayesian negative binomial models were fitted to monthly malaria incidence data, extracted from records of patients with febrile illnesses visiting the Lwak Mission Hospital be-tween 2008 and 2019. Data pertaining to bed net use and socio-economic status (SES) were obtained from household surveys. Climatic proxy variables obtained from remote sensing were included as covariates in the models. Bayesian variable selection was used to determine the elapsing time between climate suitability and malaria incidence.Results: Malaria incidence increased by 50% from 2008 to 2010, then declined by 73% until 2015. There was a resurgence of cases after 2016, despite high bed net use. Increase in daytime land surface temperature was associated with a decline in malaria incidence (incidence rate ratio [IRR] = 0.70, 95% Bayesian credible interval [BCI]: 0.59-0.82), while rainfall was associated with increased incidence (IRR = 1.27, 95% BCI: 1.10-1.44). Bed net use was associated with a decline in malaria incidence in children aged 6-59 months (IRR = 0.78, 95% BCI: 0.70-0.87) but not in older age groups, whereas SES was not associated with malaria incidence in this population.Conclusions: Variability in climatic factors showed a stronger effect on malaria incidence than bed net use. Bed net use was, however, associated with a reduction in malaria incidence, especially among children aged 6-59 months after adjusting for climate effects. To sustain the downward trend in malaria incidence, this study recommends continued distribution and use of bed nets and consideration of climate-based malaria early warning systems when planning for future control interventions.

Background: Climate change significantly impacts health in low-and middle-income countries (LMICs), exacerbating vulnerabilities. Comprehensive data for evidence-based research and decision-making is crucial but scarce. Health and Demographic Surveillance Sites (HDSSs) in Africa and Asia provide a robust infrastructure with longitudinal population cohort data, yet they lack climate-health specific data. Acquiring this information is essential for understanding the burden of climate-sensitive diseases on populations and guiding targeted policies and interventions in LMICs to enhance mitigation and adaptation capacities. Objective: The objective of this research is to develop and implement the Change and Health Evaluation and Response System (CHEERS) as a methodological framework, designed to facilitate the generation and ongoing monitoring of climate change and health-related data within existing Health and Demographic Surveillance Sites (HDSSs) and comparable research infrastructures. Methods: CHEERS uses a multi-tiered approach to assess health and environmental exposures at the individual, household, and community levels, utilizing digital tools such as wearable devices, indoor temperature and humidity measurements, remotely sensed satellite data, and 3D-printed weather stations. The CHEERS framework utilizes a graph database to efficiently manage and analyze diverse data types, leveraging graph algorithms to understand the complex interplay between health and environmental exposures. Results: The Nouna CHEERS site, established in 2022, has yielded significant preliminary findings. By using remotely-sensed data, the site has been able to predict crop yield at a household level in Nouna and explore the relationships between yield, socioeconomic factors, and health outcomes. The feasibility and acceptability of wearable technology have been confirmed in rural Burkina Faso for obtaining individual-level data, despite the presence of technical challenges. The use of wearables to study the impact of extreme weather on health has shown significant effects of heat exposure on sleep and daily activity, highlighting the urgent need for interventions to mitigate adverse health consequences. Conclusion: Implementing the CHEERS in research infrastructures can advance climate change and health research, as large and longitudinal datasets have been scarce for LMICs. This data can inform health priorities, guide resource allocation to address climate change and health exposures, and protect vulnerable communities in LMICs from these exposures.