Evidence map›Paper›PMID 35625483›Full record

ArticleBiology2022

Spatiotemporal Epidemiology of Tuberculosis in Thailand from 2011 to 2020.

Kawin Chinpong, Kaewklao Thavornwattana, Peerawich Armatrmontree, Peerut Chienwichai, Saranath Lawpoolsri, Udomsak Silachamroon, Richard J Maude, Chawarat Rotejanaprasert

Abstract read
In one paragraph

Article in Biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

8 authors.

Kawin ChinpongPrincess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok 10210, Thailand.
Kaewklao ThavornwattanaPrincess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok 10210, Thailand.
Peerawich ArmatrmontreePrincess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok 10210, Thailand.
Peerut ChienwichaiPrincess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok 10210, Thailand.ORCID 0000-0002-1088-9451
Saranath LawpoolsriDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand.ORCID 0000-0003-4841-7924
Udomsak SilachamroonDepartment of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand.
Richard J MaudeMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand.ORCID 0000-0002-5355-0562
Chawarat RotejanaprasertDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand.ORCID 0000-0003-2623-0077

Funding

Wellcome Trust 106698/Z/14/Z
6 · The paper itself

Abstract

Tuberculosis is a leading cause of infectious disease globally, especially in developing countries. Better knowledge of spatial and temporal patterns of tuberculosis burden is important for effective control programs as well as informing resource and budget allocation. Studies have demonstrated that TB exhibits highly complex dynamics in both spatial and temporal dimensions at different levels. In Thailand, TB research has been primarily focused on surveys and clinical aspects of the disease burden with little attention on spatiotemporal heterogeneity. This study aimed to describe temporal trends and spatial patterns of TB incidence and mortality in Thailand from 2011 to 2020. Monthly TB case and death notification data were aggregated at the provincial level. Age-standardized incidence and mortality were calculated; time series and global and local clustering analyses were performed for the whole country. There was an overall decreasing trend with seasonal peaks in the winter. There was spatial heterogeneity with disease clusters in many regions, especially along international borders, suggesting that population movement and socioeconomic variables might affect the spatiotemporal distribution in Thailand. Understanding the space-time distribution of TB is useful for planning targeted disease control program activities. This is particularly important in low- and middle-income countries including Thailand to help prioritize allocation of limited resources.

Indexed as

clusterspatiotemporalsurveillanceThailandtuberculosis

Identifiers

PMID35625483
PMCPMC9138531

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.