Evidence map›Paper›PMID 35300715›Full record

ArticleMalaria journal2022

Spatio-temporal modelling of malaria mortality in India from 2004 to 2013 from the Million Death Study.

Sayantee Jana, Sze Hang Fu, Hellen Gelband, Patrick Brown, Prabhat Jha

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Sayantee JanaIndian Institute of Technology, Hyderabad, India. sayantee.jana@math.iith.ac.in.ORCID http://orcid.org/0000-0002-9655-2605
Sze Hang FuDalla Lana School of Public Health, Centre for Global Health Research, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.
Hellen GelbandDalla Lana School of Public Health, Centre for Global Health Research, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.
Patrick BrownDalla Lana School of Public Health, Centre for Global Health Research, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.
Prabhat JhaDalla Lana School of Public Health, Centre for Global Health Research, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.
St. Michael's Hospital · CAIndian Institute of Teacher Education · IN

Funding

Measuring Tobacco Mortality within the Million Death Study in IndiaR01TW007939 · FIC · ST. MICHAEL'S HOSPITAL · PI JHA, PRABHAT · 2007 to 2010
$540k
FIC NIH HHS R01 TW007939NIH HHS 1R01TW007939
6 · The paper itself

Abstract

backgroundIndia 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.

methodsIn 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.

resultsThe 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.

conclusionThe 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.

Indexed as

MalariaHumansIndiaPrevalenceRural PopulationUrban PopulationIndiaMalaria mortalityMillion Death StudySpatio-temporal modelling

Identifiers

PMID35300715
PMCPMC8932160
OpenAlexW4220658761

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.