Evidence map›Paper›PMID 34199996›Full record

ArticleInternational journal of environmental research and public health2021

A Bayesian Spatio-Temporal Analysis of Malaria in the Greater Accra Region of Ghana from 2015 to 2019.

Elorm Donkor, Matthew Kelly, Cecilia Eliason, Charles Amotoh, Darren J Gray, Archie C A Clements, Kinley Wangdi

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  17. Distribution and Risk Factors of Malaria in the Greater Accra Region in Ghana.International journal of environmental research and public health · 2022
    Article
  18. Aflatoxin MScientific reports · 2022
    Article
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

7 authors.

Elorm DonkorDepartment of Global Health, Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia.ORCID 0000-0003-1029-8675
Matthew KellyDepartment of Global Health, Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia.
Cecilia EliasonDepartment of Adult Health, School of Nursing and Midwifery, College of Health Sciences, University of Ghana, Legon, P.O. Box LG43, Accra, Ghana.ORCID 0000-0001-7090-9736
Charles AmotohGreater Accra Regional Health Directorate, Ghana Health Service, P.O. Box 184, Accra, Ghana.
Darren J GrayDepartment of Global Health, Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia.
Archie C A ClementsFaculty of Health Sciences, Curtin University, Perth, WA 6102, Australia.
Kinley WangdiDepartment of Global Health, Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia.ORCID 0000-0002-8857-2665

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Greater Accra Region is the smallest of the 16 administrative regions in Ghana. It is highly populated and characterized by tropical climatic conditions. Although efforts towards malaria control in Ghana have had positive impacts, malaria remains in the top five diseases reported at healthcare facilities within the Greater Accra Region. To further accelerate progress, analysis of regionally generated data is needed to inform control and management measures at this level. This study aimed to examine the climatic drivers of malaria transmission in the Greater Accra Region and identify inter-district variation in malaria burden. Monthly malaria cases for the Greater Accra Region were obtained from the Ghanaian District Health Information and Management System. Malaria cases were decomposed using seasonal-trend decomposition, based on locally weighted regression to analyze seasonality. A negative binomial regression model with a conditional autoregressive prior structure was used to quantify associations between climatic variables and malaria risk and spatial dependence. Posterior parameters were estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. A total of 1,105,370 malaria cases were recorded in the region from 2015 to 2019. The overall malaria incidence for the region was approximately 47 per 1000 population. Malaria transmission was highly seasonal with an irregular inter-annual pattern. Monthly malaria case incidence was found to decrease by 2.3% (95% credible interval: 0.7-4.2%) for each 1 °C increase in monthly minimum temperature. Only five districts located in the south-central part of the region had a malaria incidence rate lower than the regional average at >95% probability level. The distribution of malaria cases was heterogeneous, seasonal, and significantly associated with climatic variables. Targeted malaria control and prevention in high-risk districts at the appropriate time points could result in a significant reduction in malaria transmission in the Greater Accra Region.

Indexed as

MalariaBayes TheoremGhanaHumansIncidenceSpatio-Temporal AnalysisBayesianclimaticGhanamalariamodelling

Identifiers

PMID34199996
PMCPMC8200193

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Registered trials

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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.