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Objectives: In many African countries, child mortality is higher in the rainy season than in the dry season. We investigated the effect of season on child mortality by time periods, sex and age in rural Guinea-Bissau.Methods: Bandim health project follows children under-five in a health and demographic surveillance system in rural Guinea-Bissau. We compared the mortality in the rainy season (June to November) between 1990 and 2013 with the mortality in the dry season (December to May) in Cox proportional hazards models providing rainy vs. dry season mortality rate ratios (r/d-mrr). Seasonal effects were estimated in strata defined by time periods with different frequency of vaccination campaigns, sex and age (<1 month, 1-11 months, 12-59 months). Verbal autopsies were interpreted using InterVa-4 software.Results: From 1990 to 2013, overall mortality was declined by almost two-thirds among 81 292 children (10 588 deaths). Mortality was 51% (95% ci: 45-58%) higher in the rainy season than in the dry season throughout the study period. The seasonal difference increased significantly with age, the r/d-mrr being 0.94 (0.86-1.03) among neonates, 1.57 (1.46-1.69) in post-neonatal infants and 1.83 (1.72-1.95) in under-five children (P for same effect <0.001). According to the InterVa, malaria deaths were the main reason for the seasonal mortality difference, causing 50% of all deaths in the rainy season, but only if the InterVa included season of death, making the argument self-confirmatory.Conclusion: The mortality declined throughout the study, yet rainy season continued to be associated with 51% higher overall mortality. [ABSTRACT FROM AUTHOR]

Objectives To determine patterns and risk factors for cause-specific adult mortality in rural southern Tanzania. Methods The study was a longitudinal open cohort and focused on adults aged 15-59 years between 2003 and 2007. Causes of deaths were ascertained by verbal autopsy (VA). Cox proportion hazards regression model was used to determine factors associated with cause-specific mortality over the 5-year period. Results Thousand three hundred and fifty-two of 65 548 adults died, representing a crude adult mortality rate (AMR) of 7.3 per 1000 person years of observation (PYO). VA was performed for 1132 (84%) deaths. HIV/AIDS [231 (20.4%)] was the leading cause of death followed by malaria [150 (13.2%)]. AMR for communicable disease (CD) causes was 2.49 per 1000 PYO, 1.21 per 1000 PYO for non-communicable diseases (NCD) and 0.53 per 1000 PYO for accidents/injury causes. NCD deaths increased from 16% in 2003 to 24% in 2007. High level of education was associated with a reduction in the risk of dying from NCDs. Those with primary education (HR = 0.67, 95% CI: 0.49, 0.92) and with education beyond primary school (HR = 0.11, 95% CI: 0.02, 0.40) had lower mortality than those who had no formal education. Compared with local residents, in-migrants were 1.7 (95% CI: 1.37, 2.11) times more likely to die from communicable disease causes. Conclusion NCDs are increasing as a result of demographic and epidemiological transitions taking place in most African countries including Tanzania and require attention to prevent increased triple disease burden of CD, NCD and accident/injuries. [ABSTRACT FROM AUTHOR]

Objectives To compare the cause of death distribution using the Physician Coded Verbal Autopsy approach versus the Interpreting Verbal Autopsy model, based on information from a French verbal autopsy questionnaire, in rural north-western Burkina Faso. Methods Data from 5649 verbal autopsy questionnaires reviewed by local physicians at the Nouna Health and Demographic Surveillance Site between 1998 and 2007 were considered for analyses. Information from VA interviews was extracted to create a set of standard indicators needed to run the Interpreting Verbal Autopsy model. Cause-specific mortality fractions were used to compare Physician Coded Verbal Autopsy and Interpreting Verbal Autopsy results. Results At the population level, 62.5% of causes of death using the Interpreting Verbal Autopsy model corresponded with those determined by two or three physicians. Although seven of the 10 main causes of death were present in both approaches, the comparison of percentages of single causes of death shows discrepancies, dominated by higher malaria rates found in the Physician Coded Verbal Autopsy approach. Conclusion Our results confirm that national mortality statistics, which are partly based on verbal autopsies, must be carefully interpreted. Difficulties in determining malaria as cause of death in holoendemic malaria regions might result in higher discrepancies than those in non-endemic areas. As neither Physician Coded Verbal Autopsy nor Interpreting Verbal Autopsy results represent a gold standard, uncertainty levels with either procedure are high. [ABSTRACT FROM AUTHOR]

Objective To describe options for analysing deaths with an unknown cause, which often occur in community-based studies that are used to estimate disease-specific mortality burden and trends in low-income countries. Methods Mathematical formulae were derived that accommodate deaths with an unknown cause for the disease-specific mortality rate, proportion of deaths attributable to the disease and all-cause mortality rate. Seven specific options are presented, including example calculations from a study of childhood malaria mortality in The Gambia. An algorithm is proposed to help make decisions on analysing deaths with an unknown cause. Results In the Gambian study, 25.2% of deaths had an unknown cause. Three options would result in 23.6% (minimum), 48.8% (maximum) and 28.7% (probably the best estimate) of deaths attributed to malaria. The best analysis option depends on the disease of interest: diseases for which the diagnostic method has high sensitivity and specificity (e.g., measles, neonatal tetanus) are best analysed assuming that deaths with an unknown cause never have this cause, while diseases for which specificity and/or sensitivity is low (e.g., malaria) are likely to account for some proportion of deaths with an unknown cause. Conclusions The most important aspects of analysing deaths with unknown cause are choosing appropriate assumptions, describing them explicitly and performing a sensitivity analysis. Studies of causes of death should report several key pieces of information on deaths with unknown cause to aid interpretation. [ABSTRACT FROM AUTHOR]