BackgroundThe most common method for determining cause of death is certification by physicians based either on available medical records, or where such data are not available, through verbal autopsy (VA). The physician-certification approach is costly and inconvenient; however, recent work shows the potential of a computer-based probabilistic model (InterVA) to interpret verbal autopsy data in a more convenient, consistent, and rapid way. In this study we validate separately both physician-certified verbal autopsy (PCVA) and the InterVA probabilistic model against hospital cause of death (HCOD) in adults dying in a district hospital on the coast of Kenya.MethodsBetween March 2007 and June 2010, VA interviews were conducted for 145 adult deaths that occurred at Kilifi District Hospital. The VA data were reviewed by a physician and the cause of death established. A range of indicators (including age, gender, physical signs and symptoms, pregnancy status, medical history, and the circumstances of death) from the VA forms were included in the InterVA for interpretation. Cause-specific mortality fractions (CSMF), Cohen's kappa (κ) statistic, receiver operating characteristic (ROC) curves, sensitivity, specificity, and positive predictive values were applied to compare agreement between PCVA, InterVA, and HCOD.ResultsHCOD, InterVA, and PCVA yielded the same top five underlying causes of adult deaths. The InterVA overestimated tuberculosis as a cause of death compared to the HCOD. On the other hand, PCVA overestimated diabetes. Overall, CSMF for the five major cause groups by the InterVA, PCVA, and HCOD were 70%, 65%, and 60%, respectively. PCVA versus HCOD yielded a higher kappa value (κ = 0.52, 95% confidence interval [CI]: 0.48, 0.54) than the InterVA versus HCOD which yielded a kappa (κ) value of 0.32 (95% CI: 0.30, 0.38). Overall, (κ) agreement across the three methods was 0.41 (95% CI: 0.37, 0.48). The areas under the ROC curves were 0.82 for InterVA and 0.88 for PCVA. The observed sensitivities and specificities across the five major causes of death varied from 43% to 100% and 87% to 99%, respectively, for the InterVA/PCVA against the HCOD.ConclusionBoth the InterVA and PCVA compared well with the HCOD at a population level and determined the top five underlying causes of death in the rural community of Kilifi. We hope that our study, albeit small, provides new and useful data that will stimulate further definitive work on methods of interpreting VA data.

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.

Sickle cell anemia (SCA) is the commonest severe monogenic disorders of humans. The disease has been highly characterized in high‐income countries but not in sub‐Saharan Africa where SCA is most prevalent. We conducted a retrospective cohort study of all children 0–13 years admitted from within a defined study area to Kilifi County Hospital in Kenya over a five‐year period. Children were genotyped for SCA retrospectively and incidence rates calculated with reference to population data. Overall, 576 of 18,873 (3.1%) admissions had SCA of whom the majority (399; 69.3%) were previously undiagnosed. The incidence of all‐cause hospital admission was 57.2/100 person years of observation (PYO; 95%CI 52.6–62.1) in children with SCA and 3.7/100 PYO (95%CI 3.7–3.8) in those without SCA (IRR 15.3; 95%CI 14.1–16.6). Rates were higher for the majority of syndromic diagnoses at all ages beyond the neonatal period, being especially high for severe anemia (hemoglobin <50 g/L; IRR 58.8; 95%CI 50.3–68.7), stroke (IRR 486; 95%CI 68.4–3,450), bacteremia (IRR 23.4; 95%CI 17.4–31.4), and for bone (IRR 607; 95%CI 284–1,300), and joint (IRR 80.9; 95%CI 18.1–362) infections. The use of an algorithm based on just five clinical features would have identified approximately half of all SCA cases among hospital‐admitted children with a number needed to test to identify each affected patient of only fourteen. Our study illustrates the clinical epidemiology of SCA in a malaria‐endemic environment without specific interventions. The targeted testing of hospital‐admitted children using the Kilifi Algorithm provides a pragmatic approach to early diagnosis in high‐prevalence countries where newborn screening is unavailable.

BackgroundMalaria continues to be a major cause of infectious disease mortality in tropical regions. However, deaths from malaria are most often not individually documented, and as a result overall understanding of malaria epidemiology is inadequate. INDEPTH Network members maintain population surveillance in Health and Demographic Surveillance System sites across Africa and Asia, in which individual deaths are followed up with verbal autopsies.ObjectiveTo present patterns of malaria mortality determined by verbal autopsy from INDEPTH sites across Africa and Asia, comparing these findings with other relevant information on malaria in the same regions.DesignFrom a database covering 111,910 deaths over 12,204,043 person-years in 22 sites, in which verbal autopsy data were handled according to the WHO 2012 standard and processed using the InterVA-4 model, over 6,000 deaths were attributed to malaria. The overall period covered was 1992–2012, but two-thirds of the observations related to 2006–2012. These deaths were analysed by site, time period, age group and sex to investigate epidemiological differences in malaria mortality.ResultsRates of malaria mortality varied by 1:10,000 across the sites, with generally low rates in Asia (one site recording no malaria deaths over 0.5 million person-years) and some of the highest rates in West Africa (Nouna, Burkina Faso: 2.47 per 1,000 person-years). Childhood malaria mortality rates were strongly correlated with Malaria Atlas Project estimates of Plasmodium falciparum parasite rates for the same locations. Adult malaria mortality rates, while lower than corresponding childhood rates, were strongly correlated with childhood rates at the site level.ConclusionsThe wide variations observed in malaria mortality, which were nevertheless consistent with various other estimates, suggest that population-based registration of deaths using verbal autopsy is a useful approach to understanding the details of malaria epidemiology.