Evidence map›Paper›PMID 30740249›Full record

ArticleBMJ global health2019

Spatial and temporal projections of the prevalence of active tuberculosis in Cambodia.

Kiesha Prem, Sok Heng Pheng, Alvin Kuo Jing Teo, Konstantin Evdokimov, Ei Ei Khaing Nang, Li Yang Hsu, Vonthanak Saphonn, Sivanna Tieng, Tan Eang Mao, Alex R Cook

Open access · goldAbstract read
In one paragraph

Article in BMJ global health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Finding gaps in routine TB surveillance activities in Bangladesh.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
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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

10 authors at 4 institutions in 2 countries.

Kiesha Prem *Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Sok Heng Pheng *National Center for Tuberculosis and Leprosy Control (CENAT), Ministry of Health, Phnom Penh, Cambodia.
Alvin Kuo Jing TeoSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Konstantin EvdokimovSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Ei Ei Khaing NangSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Li Yang HsuSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Vonthanak SaphonnUniversity of Health Sciences, Phnom Penh, Cambodia.
Sivanna TiengNational Center for Tuberculosis and Leprosy Control (CENAT), Ministry of Health, Phnom Penh, Cambodia.
Tan Eang MaoNational Center for Tuberculosis and Leprosy Control (CENAT), Ministry of Health, Phnom Penh, Cambodia.
Alex R CookSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Ministry of Health · KHNational University Health System · SGNational University of Singapore · SGUniversity of Health Science · KH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCambodia is among the 30 highest burden of tuberculosis (TB) countries. Active TB prevalence has been estimated using nationally representative multistage sampling that represents urban, rural and remote parts of the country, but the prevalence in non-sampled communes remains unknown. This study uses geospatial Bayesian statistics to estimate point prevalence across Cambodia, and demographic modelling that accounts for secular trends in fertility, mortality, urbanisation and prevalence rates to project the future burden of active TB.

methodsA Bayesian hierarchical model was developed for the 2011 National Tuberculosis Prevalence survey to estimate the differential effect of age, sex and geographic stratum on active TB prevalence; these estimates were then married with high-resolution geographic information system layers to project prevalence across Cambodia. Future TB projections under alternative scenarios were then derived by interfacing these estimates with an individual-based demographic model.

resultsStrong differences in risk by age and sex, together with geographically varying population structures, yielded the first estimated prevalence map at a 1 km scale. The projected number of active TB cases within the catchment area of each existing government healthcare facility was derived, together with projections to the year 2030 under three scenarios:

conclusionSynthesis of health and geographic data allows likely disease rates to be mapped at a high resolution to facilitate resource planning, while demographic modelling allows scenarios to be projected, demonstrating the need for the acceleration of control efforts to achieve a substantive impact on the future burden of TB in Cambodia.

Indexed as

geographic information systemsmathematical modellingtuberculosis

Identifiers

PMID30740249
PMCPMC6347953
OpenAlexW2911836794

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.