Evidence map›Paper›PMID 39574849›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Assessing Dengue Virus Importation Risks in Africa: A Climate and Travel-Based Model.

Jenicca Poongavanan, José Lourenço, Joseph L-H Tsui, Vittoria Colizza, Yajna Ramphal, Cheryl Baxter, Moritz U G Kraemer, Marcel Dunaiski, Tulio de Oliveira, Houriiyah Tegally

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Jenicca PoongavananCentre for Epidemic Response and innovation (CERI), Stellenbosch University, Stellenbosch, South Africa.
José LourençoBioISI (Biosystems and Integrative Sciences Institute), University of Lisbon, Lisbon, Portugal.
Joseph L-H TsuiDepartment of Biology, University of Oxford, Oxford,UK.
Vittoria ColizzaSorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Paris, France.
Yajna RamphalCentre for Epidemic Response and innovation (CERI), Stellenbosch University, Stellenbosch, South Africa.
Cheryl BaxterCentre for Epidemic Response and innovation (CERI), Stellenbosch University, Stellenbosch, South Africa.
Moritz U G KraemerDepartment of Biology, University of Oxford, Oxford,UK.
Marcel DunaiskiComputer Science Division, Department of Mathematical Sciences, Stellenbosch University, Stellenbosch, South Africa.
Tulio de OliveiraCentre for Epidemic Response and innovation (CERI), Stellenbosch University, Stellenbosch, South Africa.ORCID 0000-0002-3027-5254
Houriiyah TegallyCentre for Epidemic Response and innovation (CERI), Stellenbosch University, Stellenbosch, South Africa.

Funding

University of Washington Arboviral Research Network (UWARN)U01AI151698 · NIAID · UNIVERSITY OF WASHINGTON · PI Michael Gale, PETER MACGARR RABINOWITZ · 2020 to 2026
$13.3M
Role of Data Streams In Informing Infection Dynamics in Africa- INFORM AfricaU54TW012041 · FIC · INSTITUTE OF HUMAN VIROLOGY · PI Alash'le G. Abimiku, Tulio de Paiva Nazareth Andrade De Oliveira · 2021 to 2026
$6.9M
FIC NIH HHS U54 TW012041NIAID NIH HHS U01 AI151698Wellcome Trust
6 · The paper itself

Abstract

Background: Dengue is a significant global public health concern that poses a threat to Africa. Particularly, African countries are at risk of viral introductions through air travel connectivity with areas of South America and Asia that experience frequent explosive outbreaks. Limited reporting and diagnostic capacity hinder a comprehensive assessment of continent-wide transmission dynamics and deployment of surveillance strategies in Africa. This study aimed to identify African airports at high risk of receiving dengue infected passengers from Asia, Latin America and other African countries with high dengue incidence. Methods: The risk of dengue introduction into Africa from countries of high incidence in Africa, Latin America and within Africa was estimated based on origin-destination air travel flows and epidemic activity at origin. We produced a novel proxy for local dengue epidemic activity using a composite index of theoretical climate-driven transmission suitability and population density, which we used, along with travel information in a risk flow model, to estimate importation risk. Findings: We find that countries in East Africa face higher estimated risk of importation from Asia and other East African countries, whereas for West African countries, larger risk of importation is estimated from within the region. Some countries with high risk of importation experience low local transmission suitability which likely hampers the chances that importations lead to local transmission and establishment. Conversely, Mauritius, Uganda, Ivory Coast, Senegal, and Kenya are identified as countries susceptible to dengue introductions during periods of persistent transmission suitability. Interpretation: Our work improves data driven allocation of surveillance resources, in regions of Africa that are at high risk of dengue introduction and establishment, including from regional circulation. This will be critical in detecting and managing imported cases and can improve local response to dengue outbreaks. Funding: Rockefeller Foundation, National Institute of Health, EDCTP3 and Horizon Europe Research and Innovation, World Bank Group, Medical Research Foundation, Wellcome Trust, Google.org, Oxford Martin School Pandemic Genomics programme, John Fell Fund.

Indexed as

AfricaArbovirusesDengueIntroductionsMobilityRisk Flow

Identifiers

PMID39574849
PMCPMC11581072

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.