Evidence map›Paper›PMID 31009473›Full record

ArticlePloS one2019

Temporal, spatial and household dynamics of Typhoid fever in Kasese district, Uganda.

Bernadette Basuta Mirembe, Stella Mazeri, Rebecca Callaby, Luke Nyakarahuka, Clovice Kankya, Adrian Muwonge

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. 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
2.6field-weighted citation impact, top 11% 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, 32 citations in OpenAlex.

  1. Pooled it
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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

6 authors at 3 institutions in 2 countries.

Bernadette Basuta MirembeDepartment of Biosecurity Ecosystems and Veterinary Public Health, Makerere University, Kampala, Uganda.ORCID 0000-0001-7351-3729
Stella MazeriDivision of Genetics and Genomics, The Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom.
Rebecca CallabyDivision of Genetics and Genomics, The Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom.
Luke NyakarahukaDepartment of Biosecurity Ecosystems and Veterinary Public Health, Makerere University, Kampala, Uganda.ORCID 0000-0002-2944-9157
Clovice KankyaDepartment of Biosecurity Ecosystems and Veterinary Public Health, Makerere University, Kampala, Uganda.
Adrian MuwongeDepartment of Biosecurity Ecosystems and Veterinary Public Health, Makerere University, Kampala, Uganda.
Roslin Institute · GBMakerere University · UGAfrican Field Epidemiology Network · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Typhoid fever affects 21 million people globally, 1% of whom succumb to the disease. The social, economic and public health consequences of this disease disproportionately affect people in Africa and Asia. In order to design context specific prevention strategies, we need to holistically characterise outbreaks in these settings. In this study, we used retrospective data (2013-2016) at national and district level to characterise temporal and spatial dynamics of Typhoid fever outbreaks using time series and spatial analysis. We then selected cases matched with controls to investigate household socio-economic drivers using a conditional logistic regression model, and also developed a Typhoid fever outbreak-forecasting framework. The incidence rate of Typhoid fever at national and district level was ~ 160 and 60 cases per 100,000 persons per year, respectively, predominantly in urban areas. In Kasese district, Bwera sub-county registered the highest incidence rate, followed by Kisinga, Kitholhu and Nyakiyumbu sub-counties. The male-female case ratio at district level was at 1.68 and outbreaks occurred between the 20th and 40th week (May and October) each year following by seven weeks of precipitation. Our forecasting framework predicted outbreaks better at the district level rather than national. We identified a temporal window associated with Typhoid fever outbreaks in Kasese district, which is preceded by precipitation, flooding and displacement of people. We also observed that areas with high incidence of Typhoid fever also had high environmental contamination with limited water treatment. Taken together with the forecasting framework, this knowledge can inform the development of specific control and preparedness strategies at district and national level.

Indexed as

AdolescentAdultAgedAged, 80 and overDisease OutbreaksFamily CharacteristicsFemaleHumansHumidityIncidenceLogistic ModelsMaleMiddle AgedRetrospective StudiesRisk FactorsSalmonella

Identifiers

PMID31009473
PMCPMC6476469
OpenAlexW2942198579

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.