ArticleInternational journal of epidemiology2019
Using healthcare-seeking behaviour to estimate the number of Nipah outbreaks missed by hospital-based surveillance in Bangladesh.
Article in International journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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
24 citing papers in PubMed, 35 citations in OpenAlex.
- Post-mortem surveillance: an innovative strategy to detect and prevent spread of Nipah virus infection in humans.Emerging microbes & infections · 2026Article
- Reframing early warning for Nipah virus in Bangladesh: A shift from detection to anticipation.PLoS neglected tropical diseases · 2026Article
- A One Health approach to understanding and managing Nipah virus outbreaks.Nature microbiology · 2025Review
- The Genetic Diversity of Nipah Virus Across Spatial Scales.The Journal of infectious diseases · 2024Article
- Cost-effectiveness Analysis of Japanese Encephalitis Vaccination for Children <15 Years of Age, Bangladesh.Emerging infectious diseases · 2024Article
- Informing an investment case for Japanese encephalitis vaccine introduction in Bangladesh.Science advances · 2024Article
- Rapid diagnostic test: a critical need for outbreak preparedness and response for high priority pathogens.BMJ global health · 2024Review
- Building a pathway to One Health surveillance and response in Asian countries.Science in One Health · 2024Review
- The genetic diversity of Nipah virus across spatial scales.medRxiv : the preprint server for health sciences · 2023Article
- Tackling a global epidemic threat: Nipah surveillance in Bangladesh, 2006-2021.PLoS neglected tropical diseases · 2023Article
- Human Exposure to Bats, Rodents and Monkeys in Bangladesh.EcoHealth · 2023Article
- Characterizing Human Collective Behaviors During COVID-19 - Hong Kong SAR, China, 2020.China CDC weekly · 2023Article
- Lessons from the pandemic: Responding to emerging zoonotic viral diseases-a Keystone Symposia report.Annals of the New York Academy of Sciences · 2022Article
- Pandemic fatigue impedes mitigation of COVID-19 in Hong Kong.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Ecology, evolution and spillover of coronaviruses from bats.Nature reviews. Microbiology · 2022Review
- Clinical Cholera Surveillance Sensitivity in Bangladesh and Implications for Large-Scale Disease Control.The Journal of infectious diseases · 2021Article
- How geographic access to care shapes disease burden: The current impact of post-exposure prophylaxis and potential for expanded access to prevent human rabies deaths in Madagascar.PLoS neglected tropical diseases · 2021Article
- The Ecology of Nipah Virus in Bangladesh: A Nexus of Land-Use Change and Opportunistic Feeding Behavior in Bats.Viruses · 2021Article
- Inference of Nipah virus evolution, 1999-2015.Virus evolution · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 4 countries.
Funding
Abstract
backgroundUnderstanding the true burden of emergent diseases is critical for assessing public-health impact. However, surveillance often relies on hospital systems that only capture a minority of cases. We use the example of Nipah-virus infection in Bangladesh, which has a high case-fatality ratio and frequent person-to-person transmission, to demonstrate how healthcare-seeking data can estimate true burden.
methodsWe fit logistic-regression models to data from a population-based, healthcare-seeking study of encephalitis cases to characterize the impact of distance and mortality on attending one of three surveillance hospital sites. The resulting estimates of detection probabilities, as a function of distance and outcome, are applied to all observed Nipah outbreaks between 2007 and 2014 to estimate the true burden.
resultsThe probability of attending a surveillance hospital fell from 82% for people with fatal encephalitis living 10 km away from a surveillance hospital to 54% at 50 km away. The odds of attending a surveillance hospital are 3.2 (95% confidence interval: 1.6, 6.6) times greater for patients who eventually died (i.e. who were more severely ill) compared with those who survived. Using these probabilities, we estimated that 119 Nipah outbreaks (95% confidence interval: 103, 140)-an average of 15 outbreaks per Nipah season-occurred during 2007-14; 62 (52%) were detected.
conclusionsOur findings suggest hospital-based surveillance missed nearly half of all Nipah outbreaks. This analytical method allowed us to estimate the underlying burden of disease, which is important for emerging diseases where healthcare access may be limited.
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.