Evidence map›Paper›PMID 37307282›Full record

ArticlePLoS computational biology2023

Spatial dynamics of malaria transmission.

Sean L Wu, John M Henry, Daniel T Citron, Doreen Mbabazi Ssebuliba, Juliet Nakakawa Nsumba, Héctor M Sánchez C, Oliver J Brady, Carlos A Guerra, Guillermo A García, Austin R Carter and 6 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

10 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Climate Change and Malaria: A Call for Robust Analytics.medRxiv : the preprint server for health sciences · 2025
    Article
  7. Article
  8. Review
  9. Article
  10. 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

16 authors at 10 institutions in 5 countries.

Sean L WuInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
John M HenryInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
Daniel T CitronDepartment of Population Health, Grossman School of Medicine, New York University, New York, New York, United States of America.ORCID 0000-0002-1282-4176
Doreen Mbabazi SsebulibaDepartment of Mathematics and Statistics, Kyambogo University, Kampala, Uganda.
Juliet Nakakawa NsumbaDepartment of Mathematics, Makerere University Department of Mathematics, School of Physical Sciences, College of Natural Science, Makerere University, Kampala, Uganda.
Héctor M Sánchez CDivision of Epidemiology, School of Public Health, University of California Berkeley, Berkeley, California, United States of America.
Oliver J BradyCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0002-3235-2129
Carlos A GuerraMCD Global Health, Silver Spring, Maryland, United States of America.
Guillermo A GarcíaMCD Global Health, Silver Spring, Maryland, United States of America.ORCID 0000-0002-4430-4781
Austin R CarterInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
Heather M FergusonFaculty of Biomedical and Life Sciences, University of Glasgow, Glasgow, Scotland, United Kingdom.
Bakare Emmanuel AfolabiInternational Centre for Applied Mathematical Modelling and Data Analytics, Federal University Oye Ekiti, Ekiti State, Nigeria.
Simon I HayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.ORCID 0000-0002-0611-7272
Robert C ReinerInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.
Samson KiwareIfakara Health Institute, Dar es Salaam, Tanzania.
David L SmithInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.ORCID 0000-0003-4367-3849
University of Washington · USMedical Care Development International · USFederal University Oye Ekiti · NGIfakara Health Institute · TZKyambogo University · UGLondon School of Hygiene & Tropical Medicine · GBMakerere University · UGNew York University · USUniversity of California, Berkeley · USUniversity of Glasgow · GB

Funding

Transmission ProjectU19AI089674 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MATTHEW G DORSEY, MOSES Robert KAMYA · 2010 to 2026
$29.3M
Spatial Targeting and Adaptive Vector Control for Residual Transmission and Malaria Elimination in Urban African SettingsR01AI163398 · NIAID · UNIVERSITY OF WASHINGTON · PI SMITH, DAVID L. · 2021 to 2025
$3.2M
Medical Research Council MR/V031112/1NIAID NIH HHS R01 AI163398NIAID NIH HHS U19 AI089674
6 · The paper itself

Abstract

The Ross-Macdonald model has exerted enormous influence over the study of malaria transmission dynamics and control, but it lacked features to describe parasite dispersal, travel, and other important aspects of heterogeneous transmission. Here, we present a patch-based differential equation modeling framework that extends the Ross-Macdonald model with sufficient skill and complexity to support planning, monitoring and evaluation for Plasmodium falciparum malaria control. We designed a generic interface for building structured, spatial models of malaria transmission based on a new algorithm for mosquito blood feeding. We developed new algorithms to simulate adult mosquito demography, dispersal, and egg laying in response to resource availability. The core dynamical components describing mosquito ecology and malaria transmission were decomposed, redesigned and reassembled into a modular framework. Structural elements in the framework-human population strata, patches, and aquatic habitats-interact through a flexible design that facilitates construction of ensembles of models with scalable complexity to support robust analytics for malaria policy and adaptive malaria control. We propose updated definitions for the human biting rate and entomological inoculation rates. We present new formulas to describe parasite dispersal and spatial dynamics under steady state conditions, including the human biting rates, parasite dispersal, the "vectorial capacity matrix," a human transmitting capacity distribution matrix, and threshold conditions. An [Formula: see text] package that implements the framework, solves the differential equations, and computes spatial metrics for models developed in this framework has been developed. Development of the model and metrics have focused on malaria, but since the framework is modular, the same ideas and software can be applied to other mosquito-borne pathogen systems.

Indexed as

CulicidaeMalariaMalaria, FalciparumAdultAnimalsEcologyEcosystemHumans

Identifiers

PMID37307282
PMCPMC10289676
OpenAlexW4380303488

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.