ArticlePloS one2017
Disparities between malaria infection and treatment rates: Evidence from a cross-sectional analysis of households in Uganda.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- The 24, 2 hours initiative: a game changer in malaria mortality reduction.Malaria journal · 2025Review
- Household beliefs about malaria testing and treatment in Western Kenya: the role of health worker adherence to malaria test results.Malaria journal · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn Sub-Saharan Africa, both under-treatment and over-treatment of malaria are common since illnesses are often diagnosed and treated on the basis of symptoms. We investigate whether malaria treatment rates among febrile individuals correspond to observed patterns of malaria infection by age and by local prevalence. METHODS AND
findingsWe use data on treatment of febrile illnesses from a household survey that was conducted between March and May 2012 in 92 villages in six districts in Eastern Uganda. All household members were also tested for malaria using a rapid diagnostic test. We show that both the age of the febrile individual and the village prevalence rate are strongly associated with the odds that a febrile patient was infected with malaria, but not with the odds of ACT treatment. Compared to individuals who were aged 15 or above, febrile individuals aged 5-14 had 3.21 times the odds of testing positive for malaria (95% CI: [2.36 4.37], P<0·001), and febrile individuals who were under age 5 had 2.66 times the odds of testing positive for malaria (95% CI: [1.99 3.56], P<0·001). However, ACT treatment rates for febrile illnesses were not significantly higher for either children ages 5-14 (Unadjusted OR: 1.19, 95% CI: [0.88 1.62], P = 0.255) or children under the age of 5 (Unadjusted OR: 1.24, 95% CI: [0.92 1.68], P = 0·154). A one standard deviation increase in the village malaria prevalence rate was associated with a 2.03 times higher odds that a febrile individual under the age of five tested positive for malaria (95% CI: [1.63 2.54], p<0·001), but was not significantly associated with the odds of ACT treatment (Un-adjusted OR: 0.83, 95% CI: [0.66 1.05], P = 0·113). We present some evidence that this discrepancy may be because caregivers do not suspect a higher likelihood of malaria infection, conditional on fever, in young children or in high-prevalence villages.
conclusionOur findings suggest that households have significant mis-perceptions about malaria likelihood that may contribute to the under-treatment of malaria. Policies are needed to encourage caregivers to seek immediate diagnostic testing and treatment for febrile illnesses, particularly among young children.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.