Evidence map›Paper›PMID 40424246›Full record

ArticlePLoS neglected tropical diseases2025

Analysis and forecast of the disease burden of trachoma in China and the Global Population over 15 years of age, 1990-2021.

Chaohui Li, Hui Liu, Kai Wang

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Chaohui LiSchool of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, China.
Hui LiuCollege of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, Xinjiang, China.
Kai WangCollege of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, Xinjiang, China.ORCID 0000-0002-6224-8453

Funding

National Natural Science Foundation of ChinaPrevention and Treatment of High Incidence Diseases in Central Asia FundState Key Laboratory of PathogenesisYouth science and technology innovation talent of Tianshan Talent Training Program in Xinjiang
6 · The paper itself

Abstract

objectivesTrachoma is primarily transmitted through direct contact, and its complications-such as trichiasis and corneal opacity-significantly impair patients' quality of life and result in substantial productivity losses. This study explores the differences in disability-adjusted life years (DALYs) and prevalence of trachoma globally, across regions with varying Socio-demographic Index (SDI) levels, and in China, while also projecting future trends specific to China.

methodThis study, based on data from the Global Burden of Disease (GBD) database, utilized Joinpoint regression to analyze temporal trends in the age-standardized prevalence rate (ASPR) of trachoma in China from 1990 to 2021. The age-period-cohort (APC) model is used to estimate the net effects of age, period, and cohort on disease burden. Through decomposition analysis, the impact of aging, population growth, and epidemiological changes on trachoma disease burden is explored. In addition, the Bayesian Age-Period-Cohort (BAPC) model was used to project trends in the disability-adjusted life years (DALYs) rate and prevalence over the next 15 years, offering valuable insights for optimizing prevention and control strategies and consolidating achievements in disease elimination.

resultsFrom 1990 to 2021, the ASPR and ASDR of trachoma exhibited a consistent downward trend in China, globally, and across regions with varying SDI levels. In 2021, the crude prevalence and crude DALYs rates of trachoma in China increased with age, reaching their peak in the 70-74-year age group. Marked disparities were observed among different SDI regions, with high-SDI areas recording the lowest prevalence and DALYs burden, while low-SDI regions experienced the highest. It is expected that from 2022 to 2036, the ASPR and ASDR of male and female populations aged 15 and above in China will both show a downward trend and continue to approach 0.

conclusionThe continuous decline in the burden of trachoma disease in China from 1990 to 2021 indicates significant achievements in trachoma prevention and treatment. However, attention still needs to be paid to the elderly population aged 60 and above, and health education for the entire population should be strengthened to reduce the disease burden caused by trachoma in China.

Indexed as

Cost of IllnessTrachomaAdolescentAdultAgedAged, 80 and overChildChild, PreschoolChinaDisability-Adjusted Life YearsFemaleForecastingGlobal Burden of DiseaseGlobal HealthHumansInfant

Identifiers

PMID40424246
PMCPMC12140427

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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 Socratic graph.