ArticlePathogens (Basel, Switzerland)2023
Estimating the Directional Spread of Epidemics in Their Early Stages Using a Simple Regression Approach: A Study on African Swine Fever in Northern Italy.
Article in Pathogens (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Modelling African Swine Fever Transmission and Epidemiology: A Scoping Review of Mechanistic, Statistical, and Machine Learning Approaches.Tropical medicine and infectious disease · 2026Review
- Early African Swine Fever Dynamics in Wild Boar After Reemergence in Catalonia, Spain: Surveillance-Based Estimates of Initial Spread.Transboundary and emerging diseases · 2026Article
- Article
- Spatio-Temporal Pattern Analysis of African Swine Fever Spreading in Northwestern Italy-The Role of Habitat Interfaces.Animals : an open access journal from MDPI · 2025Article
- Exploratory Report of Wild Boar Surveillance and Epidemiological Course of African Swine Fever Outbreak; Case in the Republic of Korea From 2019 to 2023.Transboundary and emerging diseases · 2025Article
- Article
- Wild Boar Proves High Tolerance to Human-Caused Disruptions: Management Implications in African Swine Fever Outbreaks.Animals : an open access journal from MDPI · 2024Article
- The Long-Jumping of African Swine Fever: First Genotype II Notified in Sardinia, Italy.Viruses · 2023Article
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Authors and funding
4 authors.
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Abstract
The early identification of the spreading patterns of an epidemic infectious disease is an important first step towards the adoption of effective interventions. We developed a simple regression-based method to estimate the directional speed of a disease's spread, which can be easily applied with a limited dataset. We tested the method using simulation tools, then applied it on a real case study of an African Swine Fever (ASF) outbreak identified in late 2021 in northwestern Italy. Simulations showed that, when carcass detection rates were <0.1, the model produced negatively biased estimates of the ASF-affected area, with the average bias being about -10%. When detection rates were >0.1, the model produced asymptotically unbiased and progressively more predictable estimates. The model produced rather different estimates of ASF's spreading speed in different directions of northern Italy, with the average speed ranging from 33 to 90 m/day. The resulting ASF-infected areas of the outbreak were estimated to be 2216 km
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