Evidence map›Paper›PMID 36115978›Full record

ArticleMalaria journal2022

Molecular screening reveals non-uniform malaria transmission in western Kenya and absence of Rickettsia africae and selected arboviruses in hospital patients.

Tatenda Chiuya, Jandouwe Villinger, Laura C Falzon, Lorren Alumasa, Fredrick Amanya, Armanda D S Bastos, Eric M Fèvre, Daniel K Masiga

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, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
0.9field-weighted citation impact, top 31% 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, 2 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. 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

8 authors at 4 institutions in 3 countries.

Tatenda ChiuyaInternational Centre of Insect Physiology and Ecology (icipe), P.O. Box 30772-00100, Nairobi, Kenya. tchiuya@icipe.org.ORCID http://orcid.org/0000-0002-9077-7125
Jandouwe VillingerInternational Centre of Insect Physiology and Ecology (icipe), P.O. Box 30772-00100, Nairobi, Kenya.
Laura C FalzonInstitute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Chester High Road, Neston, CH64 7TE, UK.
Lorren AlumasaInternational Livestock Research Institute, Old Naivasha Road, P.O. Box 30709, Nairobi, 00100, Kenya.
Fredrick AmanyaInternational Livestock Research Institute, Old Naivasha Road, P.O. Box 30709, Nairobi, 00100, Kenya.
Armanda D S BastosDepartment of Zoology and Entomology, University of Pretoria, Private Bag 20, Pretoria, 0028, South Africa.
Eric M FèvreInstitute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Chester High Road, Neston, CH64 7TE, UK.
Daniel K MasigaInternational Centre of Insect Physiology and Ecology (icipe), P.O. Box 30772-00100, Nairobi, Kenya. dmasiga@icipe.org.
International Centre of Insect Physiology and Ecology · KEInternational Livestock Research Institute · KEUniversity of Liverpool · GBUniversity of Pretoria · ZA

Funding

Biotechnology and Biological Sciences Research Council BB/L019019/1Europen Union's Integrated Biological Control Applied Research Program DCI-FOOD/2014/346-739
6 · The paper itself

Abstract

backgroundIn sub-Saharan Africa, malaria is the common diagnosis for febrile illness and related clinical features, resulting in the under-diagnosis of other aetiologies, such as arboviruses and Rickettsia. While these may not be significant causes of mortality in malaria-endemic areas, they affect the daily life and performance of affected individuals. It is, therefore, important to have a clear picture of these other aetiologies to institute correct diagnoses at hospitals and improve patient outcomes.

methodsBlood samples were collected from patients with fever and other clinical features associated with febrile illness at selected hospitals in the malaria-endemic counties of Busia, Bungoma, and Kakamega, and screened for Crimean-Congo haemorrhagic fever, Sindbis, dengue and chikungunya viruses, Rickettsia africae, and Plasmodium spp. using high-throughput real-time PCR techniques. A logistic regression was performed on the results to explore the effect of demographic and socio-economic independent variables on malaria infection.

resultsA total of 336 blood samples collected from hospital patients between January 2018 and February 2019 were screened, of which 17.6% (59/336) were positive for Plasmodium falciparum and 1.5% (5/336) for Plasmodium malariae. Two patients had dual P. falciparum/P. malariae infections. The most common clinical features reported by the patients who tested positive for malaria were fever and headache. None of the patients were positive for the arboviruses of interest or R. africae. Patients living in Busia (OR 5.2; 95% CI 2.46-11.79; p < 0.001) and Bungoma counties (OR 2.7; 95% CI 1.27-6.16; p = 0.013) had higher odds of being infected with malaria, compared to those living in Kakamega County.

conclusionsThe reported malaria prevalence is in line with previous studies. The absence of arboviral and R. africae cases in this study may have been due to the limited number of samples screened, low-level circulation of arboviruses during inter-epidemic periods, and/or the use of PCR alone as a detection method. Other sero-surveys confirming their circulation in the area indicate that further investigations are warranted.

Indexed as

ArbovirusesMalariaRickettsiaFeverHospitalsHumansKenyaPlasmodium malariaeReal-Time Polymerase Chain ReactionDiagnosisFeverMalariaPrevalenceSocio-economic factors

Identifiers

PMID36115978
PMCPMC9482282
OpenAlexW4296248383

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.