Where do those data go? Reuse of screening results from clinical trials to estimate population prevalence of HBV infection in adults in Kilifi, Kenya

Chronic hepatitis B infection (CHB) is a significant problem worldwide with around 300 million people infected. Ambitious goals have been set towards its elimination as a public health threat by 2030. However, accurate seroprevalence estimates in many countries are lacking or fail to provide representative population estimates, particularly in the WHO African Region (AFRO). This means the full extent of HBV infection is not well described, leading to a lack of investment in diagnostics, treatment and disease prevention. Clinical trials in the WHO AFRO region have been increasing over time and many test for infectious diseases including hepatitis B virus (HBV) to determine baseline eligibility for participants, however these screening data are not reported. Here we review data from six clinical trials completed at the KEMRI-Wellcome Trust Research Programme between 2016 and 2023 that screened for HBV using hepatitis B surface antigen (HBsAg) as part of the trial exclusion criteria. 1727 people had HBsAg results available, of which 60 tested positive. We generated a crude period HBV prevalence estimate of 3.5% (95% CI 2.6-4.5%), and after standardisation for sex and age to account for the population structure of the Kilifi Health Demographics Surveillance System (KHDSS), the prevalence estimate increased to 5.0% (95% CI 3.4-6.6%). The underrepresentation of women in these trials was striking with 1263/1641 (77%) of participants being male. Alanine aminotransferase (ALT) was significantly higher in the HBsAg positive group but was not outside the normal range. We argue that routine collation and publishing of data from clinical trials could increase precision and geographical representation of global HBV prevalence estimates, enabling evidence-based provision of clinical care pathways and public health interventions to support progress towards global elimination targets. We do acknowledge when using clinical trials data for seroprevalence estimates, that local population structure data is necessary to allow standardisation of results, and the point of care tests used here are limited in sensitivity and specificity.

Impact of COVID-19 on mortality in coastal Kenya: a longitudinal open cohort study

The mortality impact of COVID-19 in Africa remains controversial because most countries lack vital registration. We analysed excess mortality in Kilifi Health and Demographic Surveillance System, Kenya, using 9 years of baseline data. SARS-CoV-2 seroprevalence studies suggest most adults here were infected before May 2022. During 5 waves of COVID-19 (April 2020-May 2022) an overall excess mortality of 4.8% (95% PI 1.2%, 9.4%) concealed a significant excess (11.6%, 95% PI 5.9%, 18.9%) among older adults ( ≥ 65 years) and a deficit among children aged 1-14 years (-7.7%, 95% PI -20.9%, 6.9%). The excess mortality rate for January 2020-December 2021, age-standardised to the Kenyan population, was 27.4/100,000 person-years (95% CI 23.2-31.6). In Coastal Kenya, excess mortality during the pandemic was substantially lower than in most high-income countries but the significant excess mortality in older adults emphasizes the value of achieving high vaccine coverage in this risk group.

SARS-CoV-2 seroprevalence and implications for population immunity: Evidence from two Health and Demographic Surveillance System sites in Kenya, February-December 2022

BACKGROUND

We sought to estimate SARS-CoV-2 antibody seroprevalence within representative samples of the Kenyan population during the third year of the COVID-19 pandemic and the second year of COVID-19 vaccine use.

METHODS

We conducted cross-sectional serosurveys among randomly selected, age-stratified samples of Health and Demographic Surveillance System (HDSS) residents in Kilifi and Nairobi. Anti-spike (anti-S) immunoglobulin G (IgG) serostatus was measured using a validated in-house ELISA and antibody concentrations estimated with reference to the WHO International Standard for anti-SARS-CoV-2 immunoglobulin.

RESULTS

HDSS residents were sampled in February-June 2022 (Kilifi HDSS N = 852; Nairobi Urban HDSS N = 851) and in August-December 2022 (N = 850 for both sites). Population-weighted coverage for ≥1 doses of COVID-19 vaccine were 11.1% (9.1-13.2%) among Kilifi HDSS residents by November 2022 and 34.2% (30.7-37.6%) among Nairobi Urban HDSS residents by December 2022. Population-weighted anti-S IgG seroprevalence among Kilifi HDSS residents increased from 69.1% (65.8-72.3%) by May 2022 to 77.4% (74.4-80.2%) by November 2022. Within the Nairobi Urban HDSS, seroprevalence by June 2022 was 88.5% (86.1-90.6%), comparable with seroprevalence by December 2022 (92.2%; 90.2-93.9%). For both surveys, seroprevalence was significantly lower among Kilifi HDSS residents than among Nairobi Urban HDSS residents, as were antibody concentrations (p < 0.001).

CONCLUSION

More than 70% of Kilifi residents and 90% of Nairobi residents were seropositive for anti-S IgG by the end of 2022. There is a potential immunity gap in rural Kenya; implementation of interventions to improve COVID-19 vaccine uptake among sub-groups at increased risk of severe COVID-19 in rural settings is recommended.

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis

Background: The Kilifi Health and Demographic Surveillance System (KHDSS) was established in 2000 to define the incidence and prevalence of local diseases and evaluate the impact of community-based interventions. KHDSS morbidity data have been reported comprehensively but mortality has not been described. This analysis describes mortality in the KHDSS over 16 years. Methods: We calculated mortality rates from 2003-2018 in four intervals of equal duration and assessed differences in mortality across these intervals by age and sex. We calculated the period survival function and median survival using the Kaplan-Meier method and mean life expectancies using abridged life tables. We estimated trend and seasonality by decomposing a time series of monthly mortality rates. We used choropleth maps and random-effects Poisson regression to investigate geographical heterogeneity. Results: Mortality declined by 36% overall between 2003-2018 and by 59% in children aged <5 years. Most of the decline occurred between 2003 and 2006. Among adults, the greatest decline (49%) was observed in those aged 15-54 years. Life expectancy at birth increased by 12 years. Females outlived males by 6 years. Seasonality was only evident in the 1-4 year age group in the first four years. Geographical variation in mortality was ±10% of the median value and did not change over time. Conclusions: Between 2003 and 2018, mortality among children and young adults has improved substantially. The steep decline in 2003-2006 followed by a much slower reduction thereafter suggests improvements in health and wellbeing have plateaued in the last 12 years. However, there is substantial inequality in mortality experience by geographical location.

Trends in inpatient and post-discharge mortality among young infants admitted to Kilifi County Hospital, Kenya: a retrospective cohort study

OBJECTIVES

To describe admission trends and estimate inpatient and post-discharge mortality and its associated exposures, among young infants (YI) admitted to a county hospital in Kenya.

DESIGN

Retrospective cohort study.

SETTING

Secondary level hospital.

PARTICIPANTS

YI aged less than 60 days admitted to hospital from January 2009 to December 2019: 12 271 admissions in 11 877 individuals. YI who were resident within a Kilifi Health and Demographic Surveillance System (KHDSS): n=3625 with 4421 admissions were followed-up for 1 year after discharge.

PRIMARY AND SECONDARY OUTCOME MEASURES

Inpatient and 1-year post-discharge mortality, the latter in KHDSS residents.

RESULTS

Of 12 271 YI admissions, 4421 (36%) were KHDSS-resident. Neonatal sepsis, preterm complications and birth asphyxia accounted for 83% of the admissions. The proportion of YI among under-5s admissions increased from 19% in 2009 to 34% in 2019 (P_trend=0.02). Inpatient case fatality was 16%, with 66% of the deaths occurring within 48 hours of admission. The introduction of free maternity care in 2013 was not associated with a change in admissions or inpatient mortality among YI. During 1-year post-discharge, 208/3625 (5.7%) YI died, 64.3 (95% CI 56.2 to 73.7) per 1000 infant-years. 49% of the post-discharge deaths occurred within 1 month of discharge, and 49% of post-discharge deaths occurred at home. Both inpatient and post-discharge deaths were associated with low admission weight. Inpatient mortality was associated with clinical signs of disease severity, while post-discharge mortality was associated with the length of hospitalisation, leaving against advice and referral to a specialised hospital.

CONCLUSIONS

YIs accounted for an increasing proportion of paediatric admissions and their overall mortality remains high. Post-discharge mortality accounts for a lower proportion of deaths but mortality rate is higher than among children aged 2-59 months. Services to address post-discharge mortality are needed and should focus on infants at higher risk.

SARS-CoV-2 seroprevalence in three Kenyan health and demographic surveillance sites, December 2020-May 2021

BACKGROUND

Most of the studies that have informed the public health response to the COVID-19 pandemic in Kenya have relied on samples that are not representative of the general population. We conducted population-based serosurveys at three Health and Demographic Surveillance Systems (HDSSs) to determine the cumulative incidence of infection with SARS-CoV-2.

METHODS

We selected random age-stratified population-based samples at HDSSs in Kisumu, Nairobi and Kilifi, in Kenya. Blood samples were collected from participants between 01 Dec 2020 and 27 May 2021. No participant had received a COVID-19 vaccine. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Locally-validated assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using classical methods and Bayesian modelling to account for the sampling scheme and assay performance.

RESULTS

We recruited 2,559 individuals from the three HDSS sites, median age (IQR) 27 (10-78) years and 52% were female. Seroprevalence at all three sites rose steadily during the study period. In Kisumu, Nairobi and Kilifi, seroprevalences (95% CI) at the beginning of the study were 36.0% (28.2-44.4%), 32.4% (23.1-42.4%), and 14.5% (9.1-21%), and respectively; at the end they were 42.0% (34.7-50.0%), 50.2% (39.7-61.1%), and 24.7% (17.5-32.6%), respectively. Seroprevalence was substantially lower among children (<16 years) than among adults at all three sites (p≤0.001).

CONCLUSION

By May 2021 in three broadly representative populations of unvaccinated individuals in Kenya, seroprevalence of anti-SARS-CoV-2 IgG was 25-50%. There was wide variation in cumulative incidence by location and age.

Incidence of chikungunya virus infections among Kenyan children with neurological disease, 2014-2018: A cohort study

BACKGROUND

Neurological complications due to chikungunya virus (CHIKV) infection have been described in different parts of the world, with children being disproportionately affected. However, the burden of CHIKV-associated neurological disease in Africa is currently unknown and given the lack of diagnostic facilities in routine care it is possible that CHIKV is an unrecognized etiology among children with encephalitis or other neurological illness.

METHODS AND FINDINGS

We estimated the incidence of CHIKV infection among children hospitalized with neurological disease in Kilifi County, coastal Kenya. We used reverse transcriptase polymerase chain reaction (RT-PCR) to systematically test for CHIKV in cerebrospinal fluid (CSF) samples from children aged <16 years hospitalized with symptoms of neurological disease at Kilifi County Hospital between January 2014 and December 2018. Clinical records were linked to the Kilifi Health and Demographic Surveillance System and population incidence rates of CHIKV infection estimated. There were 18,341 pediatric admissions for any reason during the 5-year study period, of which 4,332 (24%) had CSF collected. The most common clinical reasons for CSF collection were impaired consciousness, seizures, and coma (47%, 22%, and 21% of all collections, respectively). After acute investigations done for immediate clinical care, CSF samples were available for 3,980 admissions, of which 367 (9.2%) were CHIKV RT-PCR positive. Case fatality among CHIKV-positive children was 1.4% (95% CI 0.4, 3.2). The annual incidence of CHIKV-associated neurological disease varied between 13 to 58 episodes per 100,000 person-years among all children <16 years old. Among children aged <5 years, the incidence of CHIKV-associated neurological disease was 77 per 100,000 person-years, compared with 20 per 100,000 for cerebral malaria and 7 per 100,000 for bacterial meningitis during the study period. Because of incomplete case ascertainment due to children not presenting to hospital, or not having CSF collected, these are likely minimum estimates. Study limitations include reliance on hospital-based surveillance and limited CSF sampling in children in coma or other contraindications to lumbar puncture, both of which lead to under-ascertainment of incidence and of case fatality.

CONCLUSIONS

In this study, we observed that CHIKV infections are relatively more common than cerebral malaria and bacterial meningitis among children hospitalized with neurological disease in coastal Kenya. Given the wide distribution of CHIKV mosquito vectors, studies to determine the geographic extent of CHIKV-associated neurological disease in Africa are essential.

Seroprevalence of Antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 Among Healthcare Workers in Kenya

BACKGROUND

Few studies have assessed the seroprevalence of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among healthcare workers (HCWs) in Africa. We report findings from a survey among HCWs in 3 counties in Kenya.

METHODS

We recruited 684 HCWs from Kilifi (rural), Busia (rural), and Nairobi (urban) counties. The serosurvey was conducted between 30 July and 4 December 2020. We tested for immunoglobulin G antibodies to SARS-CoV-2 spike protein, using enzyme-linked immunosorbent assay. Assay sensitivity and specificity were 92.7 (95% CI, 87.9-96.1) and 99.0% (95% CI, 98.1-99.5), respectively. We adjusted prevalence estimates, using bayesian modeling to account for assay performance.

RESULTS

The crude overall seroprevalence was 19.7% (135 of 684). After adjustment for assay performance, seroprevalence was 20.8% (95% credible interval, 17.5%-24.4%). Seroprevalence varied significantly (P < .001) by site: 43.8% (95% credible interval, 35.8%-52.2%) in Nairobi, 12.6% (8.8%-17.1%) in Busia and 11.5% (7.2%-17.6%) in Kilifi. In a multivariable model controlling for age, sex, and site, professional cadre was not associated with differences in seroprevalence.

CONCLUSION

These initial data demonstrate a high seroprevalence of antibodies to SARS-CoV-2 among HCWs in Kenya. There was significant variation in seroprevalence by region, but not by cadre.

Sero-surveillance for IgG to SARS-CoV-2 at antenatal care clinics in three Kenyan referral hospitals: Repeated cross-sectional surveys 2020-21

INTRODUCTION

The high proportion of SARS-CoV-2 infections that have remained undetected presents a challenge to tracking the progress of the pandemic and estimating the extent of population immunity.

METHODS

We used residual blood samples from women attending antenatal care services at three hospitals in Kenya between August 2020 and October 2021and a validated IgG ELISA for SARS-Cov-2 spike protein and adjusted the results for assay sensitivity and specificity. We fitted a two-component mixture model as an alternative to the threshold analysis to estimate of the proportion of individuals with past SARS-CoV-2 infection.

RESULTS

We estimated seroprevalence in 2,981 women; 706 in Nairobi, 567 in Busia and 1,708 in Kilifi. By October 2021, 13% of participants were vaccinated (at least one dose) in Nairobi, 2% in Busia. Adjusted seroprevalence rose in all sites; from 50% (95%CI 42-58) in August 2020, to 85% (95%CI 78-92) in October 2021 in Nairobi; from 31% (95%CI 25-37) in May 2021 to 71% (95%CI 64-77) in October 2021 in Busia; and from 1% (95% CI 0-3) in September 2020 to 63% (95% CI 56-69) in October 2021 in Kilifi. Mixture modelling, suggests adjusted cross-sectional prevalence estimates are underestimates; seroprevalence in October 2021 could be 74% in Busia and 72% in Kilifi.

CONCLUSIONS

There has been substantial, unobserved transmission of SARS-CoV-2 in Nairobi, Busia and Kilifi Counties. Due to the length of time since the beginning of the pandemic, repeated cross-sectional surveys are now difficult to interpret without the use of models to account for antibody waning.

Mortality in rural coastal Kenya measured using the Kilifi Health and Demographic Surveillance System: a 16-year descriptive analysis

Background: The Kilifi Health and Demographic Surveillance System (KHDSS) was established in 2000 to define the incidence and prevalence of local diseases and evaluate the impact of community-based interventions. KHDSS morbidity data have been reported comprehensively but mortality has not been described. This analysis describes mortality in the KHDSS over 16 years. Methods: We calculated mortality rates from 2003–2018 in four intervals of equal duration and assessed differences in mortality across these intervals by age and sex. We calculated the period survival function and median survival using the Kaplan–Meier method and mean life expectancies using abridged life tables. We estimated trend and seasonality by decomposing a time series of monthly mortality rates. We used choropleth maps and random-effects Poisson regression to investigate geographical heterogeneity. Results: Mortality declined by 36% overall between 2003–2018 and by 59% in children aged <5 years. Most of the decline occurred between 2003 and 2006. Among adults, the greatest decline (49%) was observed in those aged 15–54 years. Life expectancy at birth increased by 12 years. Females outlived males by 6 years. Seasonality was only evident in the 1–4 year age group in the first four years. Geographical variation in mortality was ±10% of the median value and did not change over time. Conclusions: Between 2003 and 2018, mortality among children and young adults has improved substantially. The steep decline in 2003–2006 followed by a much slower reduction thereafter suggests improvements in health and wellbeing have plateaued in the last 12 years. However, there is substantial inequality in mortality experience by geographical location.

COVID-19 transmission dynamics underlying epidemic waves in Kenya

Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or infection spreads to susceptible subpopulations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model, we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of higher-transmissibility variants. Reopening schools led to a minor increase in transmission between the second and third waves. Socioeconomic and urban–rural population structure are critical determinants of viral transmission in Kenya.

Quantifying previous SARS-CoV-2 infection through mixture modelling of antibody levels

As countries decide on vaccination strategies and how to ease movement restrictions, estimating the proportion of the population previously infected with SARS-CoV-2 is important for predicting the future burden of COVID-19. This proportion is usually estimated from serosurvey data in two steps: first the proportion above a threshold antibody level is calculated, then the crude estimate is adjusted using external estimates of sensitivity and specificity. A drawback of this approach is that the PCR-confirmed cases used to estimate the sensitivity of the threshold may not be representative of cases in the wider population-e.g., they may be more recently infected and more severely symptomatic. Mixture modelling offers an alternative approach that does not require external data from PCR-confirmed cases. Here we illustrate the bias in the standard threshold-based approach by comparing both approaches using data from several Kenyan serosurveys. We show that the mixture model analysis produces estimates of previous infection that are often substantially higher than the standard threshold analysis.

Anti-Severe Acute Respiratory Syndrome Coronavirus 2 Immunoglobulin G Antibody Seroprevalence Among Truck Drivers and Assistants in Kenya

In October 2020, anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G seroprevalence among truck drivers and their assistants (TDA) in Kenya was 42.3%, higher than among healthcare workers and blood donors. Truck drivers and their assistants transport essential supplies during the coronavirus disease 2019 pandemic, placing them at increased risk of being infected and of transmitting SARS-CoV-2 over a wide geographical area.

Prevalence of SARS-CoV-2 Antibodies From a National Serosurveillance of Kenyan Blood Donors, January-March 2021

This study examines the prevalence of SARS-CoV-2 antibodies among blood donors aged 16 to 64 years in Kenya from January to March 2021.

Temporal trends of SARS-CoV-2 seroprevalence during the first wave of the COVID-19 epidemic in Kenya

Observed SARS-CoV-2 infections and deaths are low in tropical Africa raising questions about the extent of transmission. We measured SARS-CoV-2 IgG by ELISA in 9,922 blood donors across Kenya and adjusted for sampling bias and test performance. By 1st September 2020, 577 COVID-19 deaths were observed nationwide and seroprevalence was 9.1% (95%CI 7.6-10.8%). Seroprevalence in Nairobi was 22.7% (18.0-27.7%). Although most people remained susceptible, SARS-CoV-2 had spread widely in Kenya with apparently low associated mortality.

Endemic chikungunya fever in Kenyan children: a prospective cohort study

Background

Chikungunya fever (CHIKF) was first described in Tanzania in 1952. Several epidemics including East Africa have occurred, but there are no descriptions of longitudinal surveillance of endemic disease. Here, we estimate the incidence of CHIKF in coastal Kenya and describe the associated viral phylogeny.

Methods

We monitored acute febrile illnesses among 3500 children visiting two primary healthcare facilities in coastal Kenya over a 5-year period (2014–2018). Episodes were linked to a demographic surveillance system and blood samples obtained. Cross-sectional sampling in a community survey of a different group of 435 asymptomatic children in the same study location was done in 2016. Reverse-transcriptase PCR was used for chikungunya virus (CHIKV) screening, and viral genomes sequenced for phylogenetic analyses.

Results

We found CHIKF to be endemic in this setting, associated with 12.7% (95% CI 11.60, 13.80) of all febrile presentations to primary healthcare. The prevalence of CHIKV infections among asymptomatic children in the community survey was 0.7% (95% CI 0.22, 2.12). CHIKF incidence among children < 1 year of age was 1190 cases/100,000-person years and 63 cases/100,000-person years among children aged ≥10 years. Recurrent CHIKF episodes, associated with fever and viraemia, were observed among 19 of 170 children with multiple febrile episodes during the study period. All sequenced viral genomes mapped to the ECSA genotype albeit distinct from CHIKV strains associated with the 2004 East African epidemic.

Conclusions

CHIKF may be a substantial public health burden in primary healthcare on the East African coast outside epidemic years, and recurrent infections are common.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05875-5.

Mortality during and following hospital admission among school-aged children: a cohort study

Background: Far less is known about the reasons for hospitalization or mortality during and after hospitalization among school-aged children than among under-fives in low- and middle-income countries. This study aimed to describe common types of illness causing hospitalisation; inpatient mortality and post-discharge mortality among school-age children at Kilifi County Hospital (KCH), Kenya.

Methods: A retrospective cohort study of children 5−12 years old admitted at KCH, 2007 to 2016, and resident within the Kilifi Health Demographic Surveillance System (KHDSS). Children discharged alive were followed up for one year by quarterly census. Outcomes were inpatient and one-year post-discharge mortality.

Results: We included 3,907 admissions among 3,196 children with a median age of 7 years 8 months (IQR 74−116 months). Severe anaemia (792, 20%), malaria (749, 19%), sickle cell disease (408, 10%), trauma (408, 10%), and severe pneumonia (340, 8.7%) were the commonest reasons for admission. Comorbidities included 623 (16%) with severe wasting, 386 (10%) with severe stunting, 90 (2.3%) with oedematous malnutrition and 194 (5.0%) with HIV infection. 132 (3.4%) children died during hospitalisation. Inpatient death was associated with signs of disease severity, age, bacteraemia, HIV infection and severe stunting. After discharge, 89/2,997 (3.0%) children died within one year during 2,853 child-years observed (31.2 deaths [95%CI, 25.3−38.4] per 1,000 child-years). 63/89 (71%) of post-discharge deaths occurred within three months and 45% of deaths occurred outside hospital. Post-discharge mortality was positively associated with weak pulse, tachypnoea, severe anaemia, HIV infection and severe wasting and negatively associated with malaria. 

Conclusions: Reasons for admissions are markedly different from those reported in under-fives. There was significant post-discharge mortality, suggesting hospitalisation is a marker of risk in this population. Our findings inform guideline development to include risk stratification, targeted post-discharge care and facilitate access to healthcare to improve survival in the early months post-discharge in school-aged children.

Mortality during and following hospital admission among school-aged children: a cohort study

Background: Far less is known about the reasons for hospitalization or mortality during and after hospitalization among school-aged children than among under-fives in low- and middle-income countries. This study aimed to describe common types of illness causing hospitalisation; inpatient mortality and post-discharge mortality among school-age children at Kilifi County Hospital (KCH), Kenya. Methods: A retrospective cohort study of children 5-12 years old admitted at KCH, 2007 to 2016, and resident within the Kilifi Health Demographic Surveillance System (KHDSS). Children discharged alive were followed up for one year by quarterly census. Outcomes were inpatient and one-year post-discharge mortality. Results: We included 3,907 admissions among 3,196 children with a median age of 7 years 8 months (IQR 74-116 months). Severe anaemia (792, 20%), malaria (749, 19%), sickle cell disease (408, 10%), trauma (408, 10%), and severe pneumonia (340, 8.7%) were the commonest reasons for admission. Comorbidities included 623 (16%) with severe wasting, 386 (10%) with severe stunting, 90 (2.3%) with oedematous malnutrition and 194 (5.0%) with HIV infection. 132 (3.4%) children died during hospitalisation. Inpatient death was associated with signs of disease severity, age, bacteraemia, HIV infection and severe stunting. After discharge, 89/2,997 (3.0%) children died within one year during 2,853 child-years observed (31.2 deaths [95%CI, 25.3-38.4] per 1,000 child-years). 63/89 (71%) of post-discharge deaths occurred within three months and 45% of deaths occurred outside hospital. Post-discharge mortality was positively associated with weak pulse, tachypnoea, severe anaemia, HIV infection and severe wasting and negatively associated with malaria.  Conclusions: Reasons for admissions are markedly different from those reported in under-fives. There was significant post-discharge mortality, suggesting hospitalisation is a marker of risk in this population. Our findings inform guideline development to include risk stratification, targeted post-discharge care and facilitate access to healthcare to improve survival in the early months post-discharge in school-aged children.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Kenyan blood donors

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Africa is poorly described. The first case of SARS-CoV-2 in Kenya was reported on 12 March 2020, and an overwhelming number of cases and deaths were expected, but by 31 July 2020, there were only 20,636 cases and 341 deaths. However, the extent of SARS-CoV-2 exposure in the community remains unknown. We determined the prevalence of anti-SARS-CoV-2 immunoglobulin G among blood donors in Kenya in April-June 2020. Crude seroprevalence was 5.6% (174 of 3098). Population-weighted, test-performance-adjusted national seroprevalence was 4.3% (95% confidence interval, 2.9 to 5.8%) and was highest in urban counties Mombasa (8.0%), Nairobi (7.3%), and Kisumu (5.5%). SARS-CoV-2 exposure is more extensive than indicated by case-based surveillance, and these results will help guide the pandemic response in Kenya and across Africa.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Kenyan blood donors

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Africa is poorly described. The first case of SARS-CoV-2 in Kenya was reported on 12 March 2020, and an overwhelming number of cases and deaths were expected, but by 31 July 2020, there were only 20,636 cases and 341 deaths. However, the extent of SARS-CoV-2 exposure in the community remains unknown. We determined the prevalence of anti-SARS-CoV-2 immunoglobulin G among blood donors in Kenya in April-June 2020. Crude seroprevalence was 5.6% (174 of 3098). Population-weighted, test-performance-adjusted national seroprevalence was 4.3% (95% confidence interval, 2.9 to 5.8%) and was highest in urban counties Mombasa (8.0%), Nairobi (7.3%), and Kisumu (5.5%). SARS-CoV-2 exposure is more extensive than indicated by case-based surveillance, and these results will help guide the pandemic response in Kenya and across Africa.

Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting

BACKGROUND

Adolescents tend to experience heightened vulnerability to risky and reckless behavior. Adolescents living in rural settings may often experience poverty and a host of risk factors which can increase their vulnerability to various forms of health risk behavior (HRB). Understanding HRB clustering and its underlying factors among adolescents is important for intervention planning and health promotion. This study examines the co-occurrence of injury and violence, substance use, hygiene, physical activity, and diet-related risk behaviors among adolescents in a rural setting on the Kenyan coast. Specifically, the study objectives were to identify clusters of HRB; based on five categories of health risk behavior, and to identify the factors associated with HRB clustering.

METHODS

A cross-sectional survey was conducted of a random sample of 1060 adolescents aged 13-19 years living within the area covered by the Kilifi Health and Demographic Surveillance System. Participants completed a questionnaire on health behaviors which was administered via an Audio Computer-Assisted Self-Interview. Latent class analysis on 13 behavioral factors (injury and violence, hygiene, alcohol tobacco and drug use, physical activity, and dietary related behavior) was used to identify clustering and stepwise ordinal logistic regression with nonparametric bootstrapping identified the factors associated with clustering. The variables of age, sex, education level, school attendance, mental health, form of residence and level of parental monitoring were included in the initial stepwise regression model.

RESULTS

We identified 3 behavioral clusters (Cluster 1: Low-risk takers (22.9%); Cluster 2: Moderate risk-takers (67.8%); Cluster 3: High risk-takers (9.3%)). Relative to the cluster 1, membership of higher risk clusters (i.e. moderate or high risk-takers) was strongly associated with older age (p<0.001), being male (p<0.001), depressive symptoms (p = 0.005), school non-attendance (p = 0.001) and a low level of parental monitoring (p<0.001).

CONCLUSION

There is clustering of health risk behaviors that underlies communicable and non-communicable diseases among adolescents in rural coastal Kenya. This suggests the urgent need for targeted multi-component health behavior interventions that simultaneously address all aspects of adolescent health and well-being, including the mental health needs of adolescents.

Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System

Background: In 2014, a pilot study was conducted to test the feasibility of linking clinic attendance data for young adults at two health facilities to the population register of the Kilifi Health and Demographic Surveillance System (KHDSS). This was part of a cross-sectional survey of health problems of young people, and we tested the feasibility of using the KHDSS platform for the monitoring of future interventions.

Methods: Two facilities were used for this study. Clinical data from consenting participants aged 18-24 years were matched to KHDSS records. Data matching was achieved using national identity card numbers or otherwise using a matching algorithm based on names, sex, date of birth, location of residence and the names of other homestead members. A study form was administered to all matched patients to capture reasons for their visits and time taken to access the services. Distance to health facility from a participants’ homestead was also computed.

Results: 628 participated in the study: 386 (61%) at Matsangoni Health Centre, and 242 (39%) at Pingilikani Dispensary. 610 (97%) records were matched to the KHDSS register. Most records (605; 96%) were matched within these health facilities, while 5 (1%) were matched during homestead follow-up visits.  463 (75.9%) of those matched were women. Antenatal care (25%), family planning (13%), respiratory infections (9%) and malaria (9%) were the main reasons for seeking care. Antenatal clinic visits (n=175) and malaria (n=27) were the commonest reasons among women and men, respectively. Participants took 1-1.5 hours to access the services; 490 (81.0%) participants lived within 5 kilometres of a facility.

Conclusions: With a full-time research clerk at each health facility, linking health-facility attendance data to a longitudinal HDSS platform was feasible and could be used to monitor and evaluate the impact of health interventions on health care outcomes among young people.

The epidemiology of sickle cell disease in children recruited in infancy in Kilifi, Kenya: a prospective cohort study

BACKGROUND

Sickle cell disease is the most common severe monogenic disorder in humans. In Africa, 50-90% of children born with sickle cell disease die before they reach their fifth birthday. In this study, we aimed to describe the comparative incidence of specific clinical outcomes among children aged between birth and 5 years with and without sickle cell disease, who were resident within the Kilifi area of Kenya.

METHODS

This prospective cohort study was done on members of the Kilifi Genetic Birth Cohort Study (KGBCS) on the Indian Ocean coast of Kenya. Recruitment to the study was facilitated through the Kilifi Health and Demographic Surveillance System (KHDSS), which covers a resident population of 260 000 people, and was undertaken between Jan 1, 2006, and April 30, 2011. All children who were born within the KHDSS area and who were aged 3-12 months during the recruitment period were eligible for inclusion. Participants were tested for sickle cell disease and followed up for survival status and disease-specific admission to Kilifi County Hospital by passive surveillance until their fifth birthday. Children with sickle cell disease were offered confirmatory testing and care at a dedicated outpatient clinic.

FINDINGS

15 737 infants were recruited successfully to the KGBCS, and 128 (0·8%) of these infants had sickle cell disease, of whom 70 (54·7%) enrolled at the outpatient clinic within 12 months of recruitment. Mortality was higher in children with sickle cell disease (58 per 1000 person-years of observation, 95% CI 40-86) than in those without sickle cell disease (2·4 per 1000 person-years of observation, 2·0-2·8; adjusted incidence rate ratio [IRR] 23·1, 95% CI 15·1-35·3). Among children with sickle cell disease, mortality was lower in those who enrolled at the clinic (adjusted IRR 0·26, 95% CI 0·11-0·62) and in those with higher levels of haemoglobin F (HbF; adjusted IRR 0·40, 0·17-0·94). The incidence of admission to hospital was also higher in children with sickle cell disease than in children without sickle cell disease (210 per 1000 person-years of observation, 95% CI 174-253, vs 43 per 1000 person-years of observation, 42-45; adjusted IRR 4·80, 95% CI 3·84-6·15). The most common reason for admission to hospital among those with sickle cell disease was severe anaemia (incidence 48 per 1000 person-years of observation, 95% CI 32-71). Admission to hospital was lower in those with a recruitment HbF level above the median (IRR 0·43, 95% CI 0·24-0·78; p=0·005) and those who were homozygous for α-thalassaemia (0·07, 0·01-0·83; p=0·035).

INTERPRETATION

Although morbidity and mortality were high in young children with sickle cell disease in this Kenyan cohort, both were reduced by early diagnosis and supportive care. The emphasis must now move towards early detection and prevention of long-term complications of sickle cell disease.

FUNDING

Wellcome Trust.

Effect of ten-valent pneumococcal conjugate vaccine on invasive pneumococcal disease and nasopharyngeal carriage in Kenya: a longitudinal surveillance study

BACKGROUND

Ten-valent pneumococcal conjugate vaccine (PCV10), delivered at 6, 10, and 14 weeks of age was introduced in Kenya in January, 2011, accompanied by a catch-up campaign in Kilifi County for children aged younger than 5 years. Coverage with at least two PCV10 doses in children aged 2-11 months was 80% in 2011 and 84% in 2016; coverage with at least one dose in children aged 12-59 months was 66% in 2011 and 87% in 2016. We aimed to assess PCV10 effect against nasopharyngeal carriage and invasive pneumococcal disease (IPD) in children and adults in Kilifi County.

METHODS

This study was done at the KEMRI-Wellcome Trust Research Programme among residents of the Kilifi Health and Demographic Surveillance System, a rural community on the Kenyan coast covering an area of 891 km². We linked clinical and microbiological surveillance for IPD among admissions of all ages at Kilifi County Hospital, Kenya, which serves the community, to the Kilifi Health and Demographic Surveillance System from 1999 to 2016. We calculated the incidence rate ratio (IRR) comparing the prevaccine (Jan 1, 1999-Dec 31, 2010) and postvaccine (Jan 1, 2012-Dec 31, 2016) eras, adjusted for confounding, and reported percentage reduction in IPD as 1 minus IRR. Annual cross-sectional surveys of nasopharyngeal carriage were done from 2009 to 2016.

FINDINGS

Surveillance identified 667 cases of IPD in 3 211 403 person-years of observation. Yearly IPD incidence in children younger than 5 years reduced sharply in 2011 following vaccine introduction and remained low (PCV10-type IPD: 60·8 cases per 100 000 in the prevaccine era vs 3·2 per 100 000 in the postvaccine era [adjusted IRR 0·08, 95% CI 0·03-0·22]; IPD caused by any serotype: 81·6 per 100 000 vs 15·3 per 100 000 [0·32, 0·17-0·60]). PCV10-type IPD also declined in the post-vaccination era in unvaccinated age groups (<2 months [no cases in the postvaccine era], 5-14 years [adjusted IRR 0·26, 95% CI 0·11-0·59], and ≥15 years [0·19, 0·07-0·51]). Incidence of non-PCV10-type IPD did not differ between eras. In children younger than 5 years, PCV10-type carriage declined between eras (age-standardised adjusted prevalence ratio 0·26, 95% CI 0·19-0·35) and non-PCV10-type carriage increased (1·71, 1·47-1·99).

INTERPRETATION

Introduction of PCV10 in Kenya, accompanied by a catch-up campaign, resulted in a substantial reduction in PCV10-type IPD in children and adults without significant replacement disease. Although the catch-up campaign is likely to have brought forward the benefits by several years, the study suggests that routine infant PCV10 immunisation programmes will provide substantial direct and indirect protection in low-income settings in tropical Africa.

FUNDING

Gavi, The Vaccine Alliance and The Wellcome Trust of Great Britain.

Effect of 10-valent pneumococcal conjugate vaccine on the incidence of radiologically-confirmed pneumonia and clinically-defined pneumonia in Kenyan children: an interrupted time-series analysis

BACKGROUND

Pneumococcal conjugate vaccines (PCV) are highly protective against invasive pneumococcal disease caused by vaccine serotypes, but the burden of pneumococcal disease in low-income and middle-income countries is dominated by pneumonia, most of which is non-bacteraemic. We examined the effect of 10-valent PCV on the incidence of pneumonia in Kenya.

METHODS

We linked prospective hospital surveillance for clinically-defined WHO severe or very severe pneumonia at Kilifi County Hospital, Kenya, from 2002 to 2015, to population surveillance at Kilifi Health and Demographic Surveillance System, comprising 45 000 children younger than 5 years. Chest radiographs were read according to a WHO standard. A 10-valent pneumococcal non-typeable Haemophilus influenzae protein D conjugate vaccine (PCV10) was introduced in Kenya in January, 2011. In Kilifi, there was a three-dose catch-up campaign for infants (aged <1 year) and a two-dose catch-up campaign for children aged 1-4 years, between January and March, 2011. We estimated the effect of PCV10 on the incidence of clinically-defined and radiologically-confirmed pneumonia through interrupted time-series analysis, accounting for seasonal and temporal trends.

FINDINGS

Between May 1, 2002 and March 31, 2015, 44 771 children aged 2-143 months were admitted to Kilifi County Hospital. We excluded 810 admissions between January and March, 2011, and 182 admissions during nurses' strikes. In 2002-03, the incidence of admission with clinically-defined pneumonia was 2170 per 100 000 in children aged 2-59 months. By the end of the catch-up campaign in 2011, 4997 (61·1%) of 8181 children aged 2-11 months had received at least two doses of PCV10 and 23 298 (62·3%) of 37 416 children aged 12-59 months had received at least one dose. Across the 13 years of surveillance, the incidence of clinically-defined pneumonia declined by 0·5% per month, independent of vaccine introduction. There was no secular trend in the incidence of radiologically-confirmed pneumonia over 8 years of study. After adjustment for secular trend and season, incidence rate ratios for admission with radiologically-confirmed pneumonia, clinically-defined pneumonia, and diarrhoea (control condition), associated temporally with PCV10 introduction and the catch-up campaign, were 0·52 (95% CI 0·32-0·86), 0·73 (0·54-0·97), and 0·63 (0·31-1·26), respectively. Immediately before PCV10 was introduced, the annual incidence of clinically-defined pneumonia was 1220 per 100 000; this value was reduced by 329 per 100 000 at the point of PCV10 introduction.

INTERPRETATION

Over 13 years, admissions to Kilifi County Hospital for clinically-defined pneumonia decreased sharply (by 27%) in association with the introduction of PCV10, as did the incidence of radiologically-confirmed pneumonia (by 48%). The burden of hospital admissions for childhood pneumonia in Kilifi, Kenya, has been reduced substantially by the introduction of PCV10.

FUNDING

Gavi, The Vaccine Alliance and Wellcome Trust.

Mortality after inpatient treatment for diarrhea in children: a cohort study

BACKGROUND

There is an increasing recognition that children remain at elevated risk of death following discharge from health facilities in resource-poor settings. Diarrhea has previously been highlighted as a risk factor for post-discharge mortality.

METHODS

A retrospective cohort study was conducted to estimate the incidence and demographic, clinical, and biochemical features associated with inpatient and 1-year post-discharge mortality amongst children aged 2-59 months admitted with diarrhea from 2007 to 2015 at Kilifi County Hospital and who were residents of Kilifi Health and Demographic Surveillance System (KHDSS). Log-binomial regression was used to identify risk factors for inpatient mortality. Time at risk was from the date of discharge to the date of death, out-migration, or 365 days later. Post-discharge mortality rate was computed per 1000 child-years of observation, and Cox proportion regression used to identify risk factors for mortality.

RESULTS

Two thousand six hundred twenty-six child KHDSS residents were admitted with diarrhea, median age 13 (IQR 8-21) months, of which 415 (16%) were severely malnourished and 130 (5.0%) had a positive HIV test. One hundred twenty-one (4.6%) died in the hospital, and of 2505 children discharged alive, 49 (2.1%) died after discharge: 21.4 (95% CI 16.1-28.3) deaths per 1000 child-years. Admission with signs of both diarrhea and severe pneumonia or severe pneumonia alone had a higher risk of both inpatient and post-discharge mortality than admission for diarrhea alone. There was no significant difference in inpatient and post-discharge mortality between children admitted with diarrhea alone and those with other diagnoses excluding severe pneumonia. HIV, low mid-upper arm circumference (MUAC), and bacteremia were associated with both inpatient and post-discharge mortality. Signs of circulatory impairment, sepsis, and abnormal electrolytes were associated with inpatient but not post-discharge mortality. Prior admission and lower chest wall indrawing were associated with post-discharge mortality but not inpatient mortality. Age, stuntedness, and persistent or bloody diarrhea were not associated with mortality before or after discharge.

CONCLUSIONS

Our results accentuate the need for research to improve the uptake and outcomes of services for malnutrition and HIV as well as to elucidate causal pathways and test interventions to mitigate these risks.

Psychometric evaluation of the Major Depression Inventory among young people living in Coastal Kenya

Background: The lack of reliable, valid and adequately standardized measures of mental illnesses in sub-Saharan Africa is a key challenge for epidemiological studies on mental health.  We evaluated the psychometric properties and feasibility of using a computerized version of the Major Depression Inventory (MDI) in an epidemiological study in rural Kenya.

Methods: We surveyed 1496 participants aged 13-24 years in Kilifi County, on the Kenyan coast. The MDI was administered using a computer-assisted system, available in three languages. Internal consistency was evaluated using both Cronbach’s alpha and the Omega Coefficient. Confirmatory factor analysis was performed to evaluate the factorial structure of the MDI.

Results:  Internal consistency using both Cronbach’s Alpha (α= 0.83) and the Omega Coefficient (0.82; 95% confidence interval 0.81- 0.83) was above acceptable thresholds. Confirmatory factor analysis indicated a good fit of the data to a unidimensional model of MDI (χ ² (33, N = 1409) = 178.52 p < 0.001, TLI = 0.947, CFI = 0.961, and Root Mean Square Error of Approximation, RMSEA = .056), and this was confirmed using Item Response Models (Loevinger’s H coefficient 0.38) that proved the MDI was a unidimensional scale. Equivalence evaluation indicated invariance across sex and age groups. In our population, 3.6% of the youth presented with scores suggesting major depression using the ICD-10 scoring algorithm, and 8.7% presented with total scores indicating presence of depression (mild, moderate or severe).  Females and older youth were at the highest risk of depression.

Conclusions: The MDI has good psychometric properties.  Given its brevity, relative ease of usage and ability to identify at-risk youth, it may be useful for epidemiological studies of depression in Africa.  Studies to establish clinical thresholds for depression are recommended. The high prevalence of depressive symptoms suggests that depression may be an important public health problem in this population group.

Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System

Background: In 2014, a pilot study was conducted to test the feasibility of linking clinic attendance data for young adults at two health facilities to the population register of the Kilifi Health and Demographic Surveillance System (KHDSS). This was part of a cross-sectional survey of health problems of young people, and we tested the feasibility of using the KHDSS platform for the monitoring of future interventions. Methods: Two facilities were used for this study. Clinical data from consenting participants aged 18-24 years were matched to KHDSS records. Data matching was achieved using national identity card numbers or otherwise using a matching algorithm based on names, sex, date of birth, location of residence and the names of other homestead members. A study form was administered to all matched patients to capture reasons for their visits and time taken to access the services. Distance to health facility from a participants’ homestead was also computed. Results: 628 participated in the study: 386 (61%) at Matsangoni Health Centre, and 242 (39%) at Pingilikani Dispensary. 610 (97%) records were matched to the KHDSS register. Most records (605; 96%) were matched within these health facilities, while 5 (1%) were matched during homestead follow-up visits.  463 (75.9%) of those matched were women. Antenatal care (25%), family planning (13%), respiratory infections (9%) and malaria (9%) were the main reasons for seeking care. Antenatal clinic visits (n=175) and malaria (n=27) were the commonest reasons among women and men, respectively. Participants took 1-1.5 hours to access the services; 490 (81.0%) participants lived within 5 kilometres of a facility. Conclusions: With a full-time research clerk at each health facility, linking health-facility attendance data to a longitudinal HDSS platform was feasible and could be used to monitor and evaluate the impact of health interventions on health care outcomes among young people.

Assessing the efficiency of catch-up campaigns for the introduction of pneumococcal conjugate vaccine: a modelling study based on data from PCV10 introduction in Kilifi, Kenya

BACKGROUND

The World Health Organisation recommends the use of catch-up campaigns as part of the introduction of pneumococcal conjugate vaccines (PCVs) to accelerate herd protection and hence PCV impact. The value of a catch-up campaign is a trade-off between the costs of vaccinating additional age groups and the benefit of additional direct and indirect protection. There is a paucity of observational data, particularly from low- and middle-income countries, to quantify the optimal breadth of such catch-up campaigns.

METHODS

In Kilifi, Kenya, PCV10 was introduced in 2011 using the three-dose Expanded Programme on Immunisation infant schedule and a catch-up campaign in children <5 years old. We fitted a transmission dynamic model to detailed local data, including nasopharyngeal carriage and invasive pneumococcal disease (IPD), to infer the marginal impact of the PCV catch-up campaign over hypothetical routine cohort vaccination in that setting and to estimate the likely impact of alternative campaigns and their dose efficiency.

RESULTS

We estimated that, within 10 years of introduction, the catch-up campaign among children <5 years old prevents an additional 65 (48-84) IPD cases across age groups, compared to PCV cohort introduction alone. Vaccination without any catch-up campaign prevented 155 (121-193) IPD cases and used 1321 (1058-1698) PCV doses per IPD case prevented. In the years after implementation, the PCV programme gradually accrues herd protection, and hence its dose efficiency increases: 10 years after the start of cohort vaccination alone the programme used 910 (732-1184) doses per IPD case averted. We estimated that a two-dose catch-up among children <1 year old uses an additional 910 (732-1184) doses per additional IPD case averted. Furthermore, by extending a single-dose catch-up campaign to children aged 1 to <2 years and subsequently to those aged 2 to <5 years, the campaign uses an additional 412 (296-606) and 543 (403-763) doses per additional IPD case averted. These results were not sensitive to vaccine coverage, serotype competition, the duration of vaccine protection or the relative protection of infants.

CONCLUSIONS

We find that catch-up campaigns are a highly dose-efficient way to accelerate population protection against pneumococcal disease.

Cord blood IgG and the risk of severe Plasmodium falciparum malaria in the first year of life

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Severe malaria episodes are rare during the first few months of life.

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The rate of decay of cord blood IgG is inversely proportional to the starting concentration.

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Antibody dependent respiratory burst mediated by cord IgG protects from severe malaria during the first 6 months of infancy.

Young infants are less susceptible to severe episodes of malaria but the targets and mechanisms of protection are not clear. Cord blood antibodies may play an important role in mediating protection but many studies have examined their association with the outcome of infection or non-severe malaria. Here, we investigated whether cord blood IgG to Plasmodium falciparum merozoite antigens and antibody-mediated effector functions were associated with reduced odds of developing severe malaria at different time points during the first year of life. We conducted a case-control study of well-defined severe falciparum malaria nested within a longitudinal birth cohort of Kenyan children. We measured cord blood total IgG levels against five recombinant merozoite antigens and antibody function in the growth inhibition activity and neutrophil antibody-dependent respiratory burst assays. We also assessed the decay of maternal antibodies during the first 6 months of life. The mean antibody half-life range was 2.51 months (95% confidence interval (CI): 2.19–2.92) to 4.91 months (95% CI: 4.47–6.07). The rate of decline of maternal antibodies was inversely proportional to the starting concentration. The functional assay of antibody-dependent respiratory burst activity predicted significantly reduced odds of developing severe malaria during the first 6 months of life (Odds ratio (OR) 0.07, 95% CI: 0.007–0.74, P = 0.007). Identification of the targets of antibodies mediating antibody-dependent respiratory burst activity could contribute to the development of malaria vaccines that protect against severe episodes of malaria in early infancy.

Healthy or unhealthy migrants? Identifying internal migration effects on mortality in Africa using health and demographic surveillance systems of the INDEPTH network

Migration has been hypothesised to be selective on health but this healthy migrant hypothesis has generally been tested at destinations, and for only one type of flow, from deprived to better-off areas. The circulatory nature of migration is rarely accounted for. This study examines the relationship between different types of internal migration and adult mortality in Health and Demographic Surveillance System (HDSS) populations in West, East, and Southern Africa, and asks how the processes of selection, adaptation and propagation explain the migration-mortality relationship experienced in these contexts. The paper uses longitudinal data representing approximately 900 000 adults living in nine sub-Saharan African HDSS sites of the INDEPTH Network. Event History Analysis techniques are employed to examine the relationship between all-cause mortality and migration status, over periods ranging from 3 to 14 years for a total of nearly 4.5 million person-years. The study confirms the importance of migration in explaining variation in mortality, and the diversity of the migration-mortality relationship over a range of rural and urban local areas in the three African regions. The results confirm that the pattern of migration-mortality relationship is not exclusively explained by selection but also by propagation and adaptation. Consequences for public health policy are drawn.

Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems

Background

Estimates of the burden of disease in adults in sub-Saharan Africa largely rely on models of sparse data. We aimed to measure the burden of disease in adults living in a rural area of coastal Kenya with use of linked clinical and demographic surveillance data.

Methods

We used data from 18 712 adults admitted to Kilifi District Hospital (Kilifi, Kenya) between Jan 1, 2007, and Dec 31, 2012, linked to 790 635 person-years of observation within the Kilifi Health and Demographic Surveillance System, to establish the rates and major causes of admission to hospital. These data were also used to model disease-specific disability-adjusted life-years lost in the population. We used geographical mapping software to calculate admission rates stratified by distance from the hospital.

Findings

The main causes of admission to hospital in women living within 5 km of the hospital were infectious and parasitic diseases (303 per 100 000 person-years of observation), pregnancy-related disorders (239 per 100 000 person-years of observation), and circulatory illnesses (105 per 100 000 person-years of observation). Leading causes of hospital admission in men living within 5 km of the hospital were infectious and parasitic diseases (169 per 100 000 person-years of observation), injuries (135 per 100 000 person-years of observation), and digestive system disorders (112 per 100 000 person-years of observation). HIV-related diseases were the leading cause of disability-adjusted life-years lost (2050 per 100 000 person-years of observation), followed by non-communicable diseases (741 per 100 000 person-years of observation). For every 5 km increase in distance from the hospital, all-cause admission rates decreased by 11% (95% CI 7–14) in men and 20% (17–23) in women. The magnitude of this decline was highest for endocrine disorders in women (35%; 95% CI 22–46) and neoplasms in men (30%; 9–45).

Interpretation

Adults in rural Kenya face a combined burden of infectious diseases, pregnancy-related disorders, cardiovascular illnesses, and injuries. Disease burden estimates based on hospital data are affected by distance from the hospital, and the amount of underestimation of disease burden differs by both disease and sex.

Funding

The Wellcome Trust, GAVI Alliance.

A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots

Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or 'hotspots' of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance.DOI: http://dx.doi.org/10.7554/eLife.02130.001.