Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya.
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 uniqu...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5509217?pdf=render |
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| author | Sammy Khagayi Nyaguara Amek Godfrey Bigogo Frank Odhiambo Penelope Vounatsou |
| author_facet | Sammy Khagayi Nyaguara Amek Godfrey Bigogo Frank Odhiambo Penelope Vounatsou |
| author_sort | Sammy Khagayi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T13:19:32Z |
| format | Article |
| id | doaj.art-3594ddeec1f34af988b78a88b7464886 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-13T13:19:32Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-3594ddeec1f34af988b78a88b74648862022-12-22T02:45:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01127e018051610.1371/journal.pone.0180516Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya.Sammy KhagayiNyaguara AmekGodfrey BigogoFrank OdhiamboPenelope VounatsouThe 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.http://europepmc.org/articles/PMC5509217?pdf=render |
| spellingShingle | Sammy Khagayi Nyaguara Amek Godfrey Bigogo Frank Odhiambo Penelope Vounatsou Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya. PLoS ONE |
| title | Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya. |
| title_full | Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya. |
| title_fullStr | Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya. |
| title_full_unstemmed | Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya. |
| title_short | Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya. |
| title_sort | bayesian spatio temporal modeling of mortality in relation to malaria incidence in western kenya |
| url | http://europepmc.org/articles/PMC5509217?pdf=render |
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