Evidence map›Paper›PMID 37235591›Full record

ArticlePLoS neglected tropical diseases2023

Mapping the risk of Rift Valley fever in Uganda using national seroprevalence data from cattle, sheep and goats.

Dan Tumusiime, Emmanuel Isingoma, Optato B Tashoroora, Deo B Ndumu, Milton Bahati, Noelina Nantima, Denis Rwabiita Mugizi, Christine Jost, Bernard Bett

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 4% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

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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

9 authors at 3 institutions in 4 countries.

Dan TumusiimeMinistry of Agriculture, Animal Industry and Fisheries, Entebbe, Uganda.
Emmanuel IsingomaMinistry of Agriculture, Animal Industry and Fisheries, Entebbe, Uganda.
Optato B TashorooraMinistry of Agriculture, Animal Industry and Fisheries, Entebbe, Uganda.
Deo B NdumuMinistry of Agriculture, Animal Industry and Fisheries, Entebbe, Uganda.
Milton BahatiMinistry of Agriculture, Animal Industry and Fisheries, Entebbe, Uganda.
Noelina NantimaMinistry of Agriculture, Animal Industry and Fisheries, Entebbe, Uganda.
Denis Rwabiita MugiziInternational Livestock Research Institute, Kampala, Uganda.
Christine JostUnited States Agency for International Development's Bureau for Humanitarian Assistance 14 (USAID/BHA), Washington, D.C., United States of America.
Bernard BettInternational Livestock Research Institute, Nairobi, Kenya.ORCID 0000-0001-9376-2941
Ministry of Agriculture, Animal Industry and Fisheries · UGInternational Livestock Research Institute · KEUnited States Agency for International Development · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uganda has had repeated outbreaks of Rift Valley fever (RVF) since March 2016 when human and livestock cases were reported in Kabale after a long interval. The disease has a complex and poorly described transmission patterns which involves several mosquito vectors and mammalian hosts (including humans). We conducted a national serosurvey in livestock to determine RVF virus (RVFV) seroprevalence, risk factors, and to develop a risk map that could be used to guide risk-based surveillance and control measures. A total of 3,253 animals from 175 herds were sampled. Serum samples collected were screened at the National Animal Disease Diagnostics and Epidemiology Centre (NADDEC) using a competition multispecies anti-RVF IgG ELISA kit. Data obtained were analyzed using a Bayesian model that utilizes integrated nested Laplace approximation (INLA) and stochastic partial differential equation (SPDE) approaches to estimate posterior distributions of model parameters, and account for spatial autocorrelation. Variables considered included animal level factors (age, sex, species) and multiple environmental data including meteorological factors, soil types, and altitude. A risk map was generated by projecting fitted (mean) values, from a final model that had environmental factors onto a spatial grid that covered the entire domain. The overall RVFV seroprevalence was 11.3% (95% confidence interval: 10.2-12.3%). Higher RVFV seroprevalences were observed in older animals compared to the young, and cattle compared to sheep and goats. RVFV seroprevalence was also higher in areas that had (i) lower precipitation seasonality, (ii) haplic planosols, and (iii) lower cattle density. The risk map generated demonstrated that RVF virus was endemic in several regions including those that have not reported clinical outbreaks in the northeastern part of the country. This work has improved our understanding on spatial distribution of RVFV risk in the country as well as the expected burden of the disease in livestock.

Indexed as

Cattle DiseasesRift Valley FeverRift Valley fever virusSheep DiseasesAgedAnimalsAntibodies, ViralBayes TheoremCattleGoatsHumansLivestockSeroepidemiologic StudiesSheepUgandaAntibodies, Viral

Identifiers

PMID37235591
PMCPMC10249900
OpenAlexW4378469361

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.