Research Article: Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya

Date Published: July 13, 2017

Publisher: Public Library of Science

Author(s): Sammy Khagayi, Nyaguara Amek, Godfrey Bigogo, Frank Odhiambo, Penelope Vounatsou, Luzia Helena Carvalho.


The effect of malaria exposure on mortality using health facility incidence data as a measure of transmission has not been well investigated. Health and demographic surveillance systems (HDSS) routinely capture data on mortality, interventions and other household related indicators, offering a unique platform for estimating and monitoring the incidence-mortality relationship in space and time.

Mortality data from the HDSS located in Western Kenya collected from 2007 to 2012 and linked to health facility incidence data were analysed using Bayesian spatio-temporal survival models to investigate the relation between mortality (all-cause/malaria-specific) and malaria incidence across all age groups. The analysis adjusted for insecticide-treated net (ITN) ownership, socio-economic status (SES), distance to health facilities and altitude. The estimates obtained were used to quantify excess mortality due to malaria exposure.

Our models identified a strong positive relationship between slide positivity rate (SPR) and all-cause mortality in young children 1–4 years (HR = 4.29; 95% CI: 2.78–13.29) and all ages combined (HR = 1.55; 1.04–2.80). SPR had a strong positive association with malaria-specific mortality in young children (HR = 9.48; 5.11–37.94), however, in older children (5–14 years), it was associated with a reduction in malaria specific mortality (HR = 0.02; 0.003–0.33).

SPR as a measure of transmission captures well the association between malaria transmission intensity and all-cause/malaria mortality. This offers a quick and efficient way to monitor malaria burden. Excess mortality estimates indicate that small changes in malaria incidence substantially reduce overall and malaria specific mortality.

Partial Text

Morbidity and mortality estimates over the last decade across age groups in sub Saharan Africa (SSA) remain high compared to other regions despite an overall global reduction. The biggest burden is due to infectious diseases that largely affect children below 5 years of age with one of the main drivers of these consistently high estimates being malaria [1,2]. Recent studies and estimates show that malaria in SSA has reduced considerably, with a drop of over 37% for cases and 60% of deaths between the years 2000 and 2015 [2,3]. In western Kenya, the Kenya Medical Research InstituteCenters for Disease Control and Prevention’s Health and Demographic Surveillance System (KHDSS) has shown that between 2003 and 2010 there was a 67% reduction in malaria mortality in all ages and 70% in children below the age of 5 years even though it remains a leading cause of death [4].

Several studies have investigated the effect of malaria transmission on mortality using mostly entomologic inoculation rate or prevalence data as a measure of transmission [5,6,8]. Entomological data is quite sparse while prevalence data does not reflect seasonal variations of transmission. Our study is the first to link HDSS malaria mortality and health facility incidence data collected continuously in a well-defined geographical area. Using these datasets well aligned in space and time, we investigated SPR as a measure of transmission in relation to all-cause and malaria-specific mortality in the KHDSS area of western Kenya employing rigorous Bayesian spatio-temporal models to account for variation in space and time. We adjusted for person time observed as discrete monthly intervals, socio-economic status, ITN ownership, average distance to health facilities, altitude and year of study. In estimating excess mortality due to malaria transmission, it was noted that small changes in slide positivity rate (SPR), results in significant increases in overall mortality in this population.

Our study showed that slide positivity rate is significantly associated with all-cause/malaria-specific mortality in this region of western Kenya. By quantifying excess mortality due to malaria, we show that small changes in malaria incidence can substantially reduce deaths.




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