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Spatio-temporal modelling of malaria mortality in India from 2004 to 2013 from the Million Death Study
by
Fu, Sze Hang
, Gelband, Hellen
, Jana, Sayantee
, Brown, Patrick
, Jha, Prabhat
in
Analysis
/ Biomedical and Life Sciences
/ Biomedicine
/ Demographic aspects
/ Distribution
/ Entomology
/ Humans
/ India
/ India - epidemiology
/ Infectious Diseases
/ Malaria
/ Malaria - epidemiology
/ Malaria mortality
/ Microbiology
/ Million Death Study
/ Mortality
/ Parasitology
/ Patient outcomes
/ Prevalence
/ Public Health
/ Rural Population
/ Spatio-temporal modelling
/ Tropical Medicine
/ Urban Population
2022
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Spatio-temporal modelling of malaria mortality in India from 2004 to 2013 from the Million Death Study
by
Fu, Sze Hang
, Gelband, Hellen
, Jana, Sayantee
, Brown, Patrick
, Jha, Prabhat
in
Analysis
/ Biomedical and Life Sciences
/ Biomedicine
/ Demographic aspects
/ Distribution
/ Entomology
/ Humans
/ India
/ India - epidemiology
/ Infectious Diseases
/ Malaria
/ Malaria - epidemiology
/ Malaria mortality
/ Microbiology
/ Million Death Study
/ Mortality
/ Parasitology
/ Patient outcomes
/ Prevalence
/ Public Health
/ Rural Population
/ Spatio-temporal modelling
/ Tropical Medicine
/ Urban Population
2022
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Spatio-temporal modelling of malaria mortality in India from 2004 to 2013 from the Million Death Study
by
Fu, Sze Hang
, Gelband, Hellen
, Jana, Sayantee
, Brown, Patrick
, Jha, Prabhat
in
Analysis
/ Biomedical and Life Sciences
/ Biomedicine
/ Demographic aspects
/ Distribution
/ Entomology
/ Humans
/ India
/ India - epidemiology
/ Infectious Diseases
/ Malaria
/ Malaria - epidemiology
/ Malaria mortality
/ Microbiology
/ Million Death Study
/ Mortality
/ Parasitology
/ Patient outcomes
/ Prevalence
/ Public Health
/ Rural Population
/ Spatio-temporal modelling
/ Tropical Medicine
/ Urban Population
2022
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Spatio-temporal modelling of malaria mortality in India from 2004 to 2013 from the Million Death Study
Journal Article
Spatio-temporal modelling of malaria mortality in India from 2004 to 2013 from the Million Death Study
2022
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Overview
Background
India has a substantial burden of malaria, concentrated in specific areas and population groups. Spatio-temporal modelling of deaths due to malaria in India is a critical tool for identifying high-risk groups for effective resource allocation and disease control policy-making, and subsequently for the country’s progress towards United Nations 2030 Sustainable Development Goals.
Methods
In this study, a spatio-temporal model with the objective of understanding the spatial distribution of malaria mortality rates and the rate of temporal decline, across the country, has been constructed. A spatio-temporal “random slope” model was used, with malaria risk depending on a spatial relative risk surface and a linear time effect with a spatially-varying coefficient. The models were adjusted for urban/rural status (residence of the deceased) and Normalized Difference Vegetation Index (NDVI), using 2004–13 data from the Million Death Study (MDS) (the most recent data available), with nationwide geographic coverage. Previous studies based on MDS had focused only on aggregated analyses.
Results
The rural population had twice the risk of death due to malaria compared to the urban population. Malaria mortality in some of the highest-risk regions, namely the states of Odisha and Jharkhand, are declining faster than other areas; however, the rate of decline was not uniformly correlated with the level of risk. The overall decline was faster after 2010.
Conclusion
The results suggest a need for increased attention in high-risk rural populations, which already face challenges like inadequate infrastructure, inaccessibility to health care facilities, awareness, and education around malaria mortality and prevalence. It also points to the urgent need to restart the MDS to document changes since 2013, to develop appropriate malaria control measures.
Publisher
BioMed Central,BioMed Central Ltd,BMC
Subject
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