ArticleNature communications2018
Substantiating freedom from parasitic infection by combining transmission model predictions with disease surveys.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Sub-national modelling of surveillance sensitivity to inform declaration of disease elimination: A retrospective validation against the elimination of wild poliovirus in Nigeria.PLoS computational biology · 2026Article
- Monitoring Pathogens in Free-Living Large Herbivores in a Nature Reserve in the Netherlands.Transboundary and emerging diseases · 2025Article
- Community-Directed Vector Control to Accelerate Onchocerciasis Elimination.Pathogens (Basel, Switzerland) · 2024Review
- Review state-of-the-art of output-based methodological approaches for substantiating freedom from infection.Frontiers in veterinary science · 2024Review
- Evaluating elimination thresholds and stopping criteria for interventions against the vector-borne macroparasitic disease, lymphatic filariasis, using mathematical modelling.Communications biology · 2023Article
- Universal Polymerase Chain Reaction and Antibody Testing Demonstrate Little to No Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in a Rural Community.Open forum infectious diseases · 2021Article
- Universal PCR and antibody testing demonstrate little to no transmission of SARS-CoV-2 in a rural community.medRxiv : the preprint server for health sciences · 2020Article
- Finding hotspots: development of an adaptive spatial sampling approach.Scientific reports · 2020Article
- Predicting lymphatic filariasis elimination in data-limited settings: A reconstructive computational framework for combining data generation and model discovery.PLoS computational biology · 2020Article
- Base protocol for real time active random surveillance of coronavirus disease (COVID-19) - Adapting veterinary methodology to public health.One health (Amsterdam, Netherlands) · 2020Article
- Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness.Scientific reports · 2020Article
- Assessment of control strategies against Clonorchis sinensis infection based on a multi-group dynamic transmission model.PLoS neglected tropical diseases · 2020Article
- Evaluating the Evidence for Lymphatic Filariasis Elimination.Trends in parasitology · 2019Review
- Accelerating river blindness elimination by supplementing MDA with a vegetation "slash and clear" vector control strategy: a data-driven modeling analysis.Scientific reports · 2019Article
- Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- The roadmap towards elimination of lymphatic filariasis by 2030: insights from quantitative and mathematical modelling.Gates open research · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
13 authors.
Funding
Abstract
Stopping interventions is a critical decision for parasite elimination programmes. Quantifying the probability that elimination has occurred due to interventions can be facilitated by combining infection status information from parasitological surveys with extinction thresholds predicted by parasite transmission models. Here we demonstrate how the integrated use of these two pieces of information derived from infection monitoring data can be used to develop an analytic framework for guiding the making of defensible decisions to stop interventions. We present a computational tool to perform these probability calculations and demonstrate its practical utility for supporting intervention cessation decisions by applying the framework to infection data from programmes aiming to eliminate onchocerciasis and lymphatic filariasis in Uganda and Nigeria, respectively. We highlight a possible method for validating the results in the field, and discuss further refinements and extensions required to deploy this predictive tool for guiding decision making by programme managers.
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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 OpenQuestion graph.