Evidence map›Paper›PMID 34857842›Full record

ArticleScientific reports2021

Low parasite connectivity among three malaria hotspots in Thailand.

Hsiao-Han Chang, Meng-Chun Chang, Mathew Kiang, Ayesha S Mahmud, Nattwut Ekapirat, Kenth Engø-Monsen, Prayuth Sudathip, Caroline O Buckee, Richard J Maude

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Epidemiological Changes in Acute Febrile Diseases after the COVID-19 Pandemic in Thailand.The American journal of tropical medicine and hygiene · 2025
    Article
  4. Article
  5. Low Genetic Diversity ofTropical medicine and infectious disease · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

9 authors.

Hsiao-Han ChangInstitute of Bioinformatics and Structural Biology and Department of Life Science, National Tsing Hua University, Hsinchu, Taiwan. hhchang@life.nthu.edu.tw.
Meng-Chun ChangInstitute of Bioinformatics and Structural Biology and Department of Life Science, National Tsing Hua University, Hsinchu, Taiwan.
Mathew KiangDepartment of Epidemiology and Population Health, Stanford University, Stanford, CA, USA.
Ayesha S MahmudDepartment of Demography, University of California, Berkeley, USA.
Nattwut EkapiratMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Kenth Engø-MonsenTelenor Research, Oslo, Norway.
Prayuth SudathipDivision of Vector Borne Diseases, Ministry of Public Health, Nonthaburi, Thailand.
Caroline O Buckee *Harvard TH Chan School of Public Health, Harvard University, Boston, USA.
Richard J Maude *Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. richard@tropmedres.ac.

Funding

New approaches to measuring and containing the spatial spread of human pathogensR35GM124715 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI BUCKEE, CAROLINE O'FLAHERTY · 2017 to 2021
$2.0M
NIGMS NIH HHS R35 GM124715Wellcome Trust 202101Wellcome Trust 220211
6 · The paper itself

Abstract

Identifying sources and sinks of malaria transmission is critical for designing effective intervention strategies particularly as countries approach elimination. The number of malaria cases in Thailand decreased 90% between 2012 and 2020, yet elimination has remained a major public health challenge with persistent transmission foci and ongoing importation. There are three main hotspots of malaria transmission in Thailand: Ubon Ratchathani and Sisaket in the Northeast; Tak in the West; and Yala in the South. However, the degree to which these hotspots are connected via travel and importation has not been well characterized. Here, we develop a metapopulation model parameterized by mobile phone call detail record data to estimate parasite flow among these regions. We show that parasite connectivity among these regions was limited, and that each of these provinces independently drove the malaria transmission in nearby provinces. Overall, our results suggest that due to the low probability of domestic importation between the transmission hotspots, control and elimination strategies can be considered separately for each region.

Indexed as

Cell PhoneHuman MigrationHumansMalaria, FalciparumPlasmodium falciparumPopulation SurveillanceRisk FactorsThailandTravel

Identifiers

PMID34857842
PMCPMC8640040

What OpenQuestion holds

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LicenceCC BY
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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.