Inapparent infections and cholera dynamics
Nature·
- DOI
- 10.1038/nature07084
- PMID
- 18704085
- PMCID
- —
- OpenAlex
- W1966116088
- Study type
- Journal article
- Publisher
- Springer Science and Business Media LLC
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The findings suggest that inapparent infections are central to interpreting cholera outbreak patterns and that environmental sources may be critical to sustaining endemicity, with implications for transmission theory and control strategies.
Structured evidence summary
Research question
The study investigates how the proportion of asymptomatic infections and characteristics of immunity shape cholera transmission dynamics, using long-term mortality records.
Study design
A mechanistic modeling study that fits a dynamical transmission model incorporating human and environmental infection sources, multiple infection outcomes, seasonality, process noise, hidden variables, and measurement error to mortality time-series data using maximum likelihood methods.
Population and setting
The analysis uses approximately 50 years of mortality data from 26 districts of Bengal, India, described as the endemic home of cholera.
Main findings
A model with a high asymptomatic-to-symptomatic ratio and rapidly waning immunity fits 50 years of Bengal mortality data. The authors report that the asymptomatic ratio is higher than previously assumed, that immunity from mild infections wanes faster than earlier analyses suggested, and that the environmental reservoir directly accounts for relatively few infections but may be important for endemicity.
Public-health relevance
The findings suggest that inapparent infections are central to interpreting cholera outbreak patterns and that environmental sources may be critical to sustaining endemicity, with implications for transmission theory and control strategies.
Important limitations
The summary is limited to the supplied single-article abstract/metadata and requires the original paper for decision-grade interpretation. The abstract does not explicitly enumerate limitations of the modeling assumptions, parameter identifiability, or generalizability beyond the studied districts.
GIDS interpretation
This article is relevant to cholera transmission dynamics and environmental reservoirs in an endemic Indian setting and may aid discoverability of mechanistic modeling approaches for cholera, but no connection to any live surveillance signal can be drawn from the supplied evidence.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 9 auditable classifier relationships to diseases, places, topics, and study design.