Evidence map›Paper›PMID 42738599›Full record

ArticleAnimals : an open access journal from MDPI2026

Quantifying ASF Outbreak Dynamics in the Philippines (2019-2023) Using Joinpoint Regression and the Estimated Dissemination Ratio.

Samuel Joseph M Castro, Roderick T Salvador, Romeo S Gundran, Janice S Garcia, Supitchaya Siriyakhun, Jakkawat Pongsumpan, Kannika Na-Lampang

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Samuel Joseph M CastroFaculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand.
Roderick T SalvadorCollege of Veterinary Science and Medicine, Central Luzon State University, Science City of Muñoz 3120, Nueva Ecija, Philippines.
Romeo S GundranCollege of Veterinary Science and Medicine, Central Luzon State University, Science City of Muñoz 3120, Nueva Ecija, Philippines.ORCID 0000-0002-9613-2491
Janice S GarciaBureau of Animal Industry, Animal Health and Welfare Division, Quezon City 1128, Metro Manila, Philippines.
Supitchaya SiriyakhunFaculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand.
Jakkawat PongsumpanFaculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand.
Kannika Na-LampangFaculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand.ORCID 0000-0003-4621-9764

Funding

Chiang Mai University
6 · The paper itself

Abstract

African swine fever (ASF) remains a major constraint on swine production in the Philippines, but interpretation of its national trajectory is complicated by changes in surveillance effort and regional heterogeneity. We analyzed domestic-pig surveillance records from August 2019 through December 2023. After exact-row deduplication and validity screening, 50,852 laboratory records were retained, including 8929 ASF-positive records and 324,741 tested samples. Monthly positive-record counts, annual and surveillance-stream-specific sample positivity, geographic and regional trajectories, year-standardized seasonality indices, Bayesian Information Criterion-selected joinpoint regression, and sliding-window Estimated Dissemination Ratios (EDRs) were evaluated. Positive laboratory records peaked at 733 in September 2020. Annual sample positivity reached 20.6% in 2020 and declined to 3.9% in 2023, despite tested-sample volume increasing from 41,035 to 102,333. Regional peaks were staggered from 2020 through 2023, demonstrating asynchronous detected activity. September and October had the highest mean seasonality indices, although their 95% confidence intervals included 1. The selected joinpoint model identified breakpoints in June, September, and December 2020 and August 2022. A first-order autoregressive correlation structure (AR(1)) sensitivity model supported the 2020 changes but not the August 2022 change. The primary 14-day EDR identified 25 sustained expansion and 28 sustained contraction episodes; 7-day estimates were more volatile, whereas 14- and 21-day estimates were more concordant. These findings indicate a transition from intense nationally detected activity in 2020 to lower sample positivity but persistent, recurrent, and regionally heterogeneous activity through 2023. Integrating record counts, testing denominators, regional patterns, joinpoint regression, and EDR provides a reproducible surveillance framework, but does not estimate population prevalence, causal policy effects, or future transmission.

Indexed as

African swine fever (ASF)joinpoint regressionspatiotemporal dynamics

Identifiers

PMID42738599
PMCPMC13564805

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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.