Evidence map›Paper›PMID 27114294›Full record

ArticleThe American journal of tropical medicine and hygiene2016

High-Resolution Plasmodium falciparum Malaria Risk Mapping in Mutasa District, Zimbabwe: Implications for Regaining Control.

Mufaro Kanyangarara, Edmore Mamini, Sungano Mharakurwa, Shungu Munyati, Lovemore Gwanzura, Tamaki Kobayashi, Timothy Shields, Luke C Mullany, Susan Mutambu, Peter R Mason and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in The American journal of tropical medicine and hygiene, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 19% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

13 authors at 3 institutions in 2 countries.

Mufaro KanyangararaDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. mkanyan1@jhu.edu.
Edmore MaminiBiomedical Research and Training Institute, Harare, Zimbabwe.
Sungano MharakurwaBiomedical Research and Training Institute, Harare, Zimbabwe.
Shungu MunyatiBiomedical Research and Training Institute, Harare, Zimbabwe.
Lovemore GwanzuraDepartment of Medical Laboratory Sciences, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe.
Tamaki KobayashiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
Timothy ShieldsDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
Luke C MullanyDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
Susan MutambuNational Institute of Health Research, Harare, Zimbabwe.
Peter R MasonBiomedical Research and Training Institute, Harare, Zimbabwe.
Frank C CurrieroDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
William J Moss
Southern Africa International Centers of Excellence for Malaria Research
Johns Hopkins University · USBiomedical Research and Training Institute · ZWUniversity of Zimbabwe · ZW

Funding

TransmissionU19AI089680 · NIAID · JOHNS HOPKINS UNIVERSITY · PI WILLIAM J MOSS · 2010 to 2026
$25.6M
NIAID NIH HHS U19 AI089680
6 · The paper itself

Abstract

In Zimbabwe, more than half of malaria cases are concentrated in Manicaland Province, where seasonal malaria epidemics occur despite intensified control strategies. The objectives of this study were to develop a prediction model based on environmental risk factors and obtain seasonal malaria risk maps for Mutasa District, one of the worst affected districts in Manicaland Province. From October 2012 to September 2015, 483 households were surveyed, and 104 individuals residing within 69 households had positive rapid diagnostic test results. Logistic regression was used to model the probability of household positivity as a function of the environmental covariates extracted from high-resolution remote sensing data sources. Model predictions and prediction standard errors were generated for the rainy and dry seasons. The resulting maps predicted elevated risk during the rainy season, particularly in low-lying areas bordering Mozambique. In contrast, the risk of malaria was low across the study area during the dry season with foci of malaria risk scattered along the northern and western peripheries of the study area. These findings underscore the need for strong cross-border malaria control initiatives to complement country-specific interventions.

Indexed as

AdolescentAntimalarialsArtemisininsChildFamily HealthFemaleHumansLogistic ModelsMalaria, FalciparumMaleMultivariate AnalysisPlasmodium falciparumPrevalenceRainRisk FactorsSeasonsAntimalarialsArtemisinins

Identifiers

PMID27114294
PMCPMC4944678
OpenAlexW2343944106

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.