ArticleThe Journal of infectious diseases2014
The seasonality of tuberculosis, sunlight, vitamin D, and household crowding.
Article in The Journal of infectious diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
61 citing papers in PubMed, 3 syntheses or guidelines pooled it, 113 citations in OpenAlex.
- Association of vitamin D receptor genetic variants with therapeutic response in multidrug-resistant pulmonary tuberculosis: a systematic review.Frontiers in cellular and infection microbiology · 2026Pooled it
- Vitamin D status and risk of incident tuberculosis disease: A nested case-control study, systematic review, and individual-participant data meta-analysis.PLoS medicine · 2019Pooled it
- Drivers of Seasonal Variation in Tuberculosis Incidence: Insights from a Systematic Review and Mathematical Model.Epidemiology (Cambridge, Mass.) · 2018Pooled it
- Beyond bacilli: integrating the microbiome into the TB research agenda.Gut microbes · 2026Review
- Data-driven model analysis of the impact of environmental and socioeconomic factors on tuberculosis incidence.Infectious Disease Modelling · 2026Article
- Weather elements and the risk of tuberculosis incidence in China from 2005 to 2019: a county-level large observational study.Journal of global health · 2026Observational
- Seasonality and mycobacterial infectious diseases in animals and humans: is there a generality of seasonal patterns for mycobacterial infections?Infectious diseases of poverty · 2025Review
- Epidemiological Profile andInternational journal of microbiology · 2025Article
- Analyzing the seasonality of tuberculosis case notifications in the UK, 2000-2018.Epidemiology and infection · 2024Article
- Pulmonary Tuberculosis Notification Rate Within Shenzhen, China, 2010-2019: Spatial-Temporal Analysis.JMIR public health and surveillance · 2024Article
- The impact of meteorological factors on tuberculosis incidence in Spain: a spatiotemporal analysis.Epidemiology and infection · 2024Article
- Ecological-level factors associated with tuberculosis incidence and mortality: A systematic review and meta-analysis.PLOS global public health · 2024Article
- Spatiotemporal and Seasonal Trends of Class A and B Notifiable Infectious Diseases in China: Retrospective Analysis.JMIR public health and surveillance · 2023Article
- Spatial-temporal analysis of pulmonary tuberculosis in Hubei Province, China, 2011-2021.PloS one · 2023Article
- Article
- Association between climate variables and pulmonary tuberculosis incidence in Brunei Darussalam.Scientific reports · 2022Article
- Article
- Distribution of bacteriologically positive and bacteriologically negative pulmonary tuberculosis in Northwest China: spatiotemporal analysis.Scientific reports · 2022Article
- Space-Time Distribution Characteristics of Tuberculosis and Its Socioeconomic Factors in Southern China from 2015 to 2019.Infection and drug resistance · 2022Article
- Short-term effects of ambient air pollution and meteorological factors on tuberculosis in semi-arid area, northwest China: a case study in Lanzhou.Environmental science and pollution research international · 2021Article
1 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 4 countries.
Funding
Abstract
backgroundUnlike other respiratory infections, tuberculosis diagnoses increase in summer. We performed an ecological analysis of this paradoxical seasonality in a Peruvian shantytown over 4 years.
methodsTuberculosis symptom-onset and diagnosis dates were recorded for 852 patients. Their tuberculosis-exposed cohabitants were tested for tuberculosis infection with the tuberculin skin test (n = 1389) and QuantiFERON assay (n = 576) and vitamin D concentrations (n = 195) quantified from randomly selected cohabitants. Crowding was calculated for all tuberculosis-affected households and daily sunlight records obtained.
resultsFifty-seven percent of vitamin D measurements revealed deficiency (<50 nmol/L). Risk of deficiency was increased 2.0-fold by female sex (P < .001) and 1.4-fold by winter (P < .05). During the weeks following peak crowding and trough sunlight, there was a midwinter peak in vitamin D deficiency (P < .02). Peak vitamin D deficiency was followed 6 weeks later by a late-winter peak in tuberculin skin test positivity and 12 weeks after that by an early-summer peak in QuantiFERON positivity (both P < .04). Twelve weeks after peak QuantiFERON positivity, there was a midsummer peak in tuberculosis symptom onset (P < .05) followed after 3 weeks by a late-summer peak in tuberculosis diagnoses (P < .001).
conclusionsThe intervals from midwinter peak crowding and trough sunlight to sequential peaks in vitamin D deficiency, tuberculosis infection, symptom onset, and diagnosis may explain the enigmatic late-summer peak in tuberculosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.