Descriptive epidemiology and spatial analysis of African swine fever epidemics in Can Tho, Vietnam, 2019.

The objectives of this study were to describe the epidemiology of African swine fever (ASF) and to identify factors that increased commune-level risk for ASF in Can Tho, a province in the Mekong River Delta of Vietnam. In 2019, a total of 2377 of the 5220 pig farms in Can Tho were ASF positive, an incidence risk of 46 (95% CI 44-47) ASF positive farms for every 100 farms at risk. Throughout the outbreak ASF resulted in either the death or culling of 59,529 pigs out of a total population size of 124,516 (just under half of the total pig population, 48%). After the first detection in Can Tho in May 2019, ASF spread quickly across all districts with an estimated dissemination ratio (EDR) of greater than one up until the end of July 2019. A mixed-effects Poisson regression model was developed to identify risk factors for ASF. One hundred unit increases in the number of pigs per square kilometre was associated with a 1.28 (95% CrI 1.05-1.55) fold increase in commune-level ASF incidence rate. One unit increases in the number of pig farms per square kilometre was associated with a 0.91 (95% CrI 0.84-0.99) decrease in commune-level ASF incidence rate. Mapping spatially contiguous communes with elevated (unaccounted-for) ASF risk provide a means for generating hypotheses for continued disease transmission. We propose that the analyses described in this paper might be run on an ongoing basis during an outbreak and disease control efforts modified in light of the information provided.

Detection of influenza epidemics using hidden Markov and Serfling approaches.

OBJECTIVE: Detection of epidemics is a critical issue in epidemiology of infectious diseases which enable healthcare system to better control it. This study is devoted to investigating the 5-year trend in influenza and severe acute respiratory infection cases in Iran. The epidemics were also detected using the hidden Markov model (HMM) and Serfling model. STUDY DESIGN: In this study, we used SARI data reported in the World Health Organization (WHO) FluNet web-based tool from August 2011 to August 2016. METHODS: SARI data in Iran from August 2011 to August 2016 were used. We applied the HMM and Serfling model for indicating the two epidemic and non-epidemic phases. The registered outbreak activity recorded on the WHO website was used as the gold standard. The coefficient of determination was reported to compare the goodness of fit of the models. RESULTS: Serfling models modified by 30% and 35% of the data had a sensitivity of 91.67% and 95.83%, while for 15%, 20% and 25% were 70.83%, 79.17% and 83.33%, respectively. Sensitivity of HMM and autoregressive HMM (AHMM) was 66.67% and 92.86%. All fitted models have a specificity of over 96%. The R2 for HMM and AHMM was calculated 0.73 and 0.85, respectively, showing better fitness of these models, while R2 was around 50% for different types of Serfling models. CONCLUSIONS: Both modified Serfling and HMM were acceptable models in determining the epidemic points for the detection of weekly SARI. The AHMM had better fitness, higher detection power and more accurate detection of the incidence of epidemics than Serfling model and high sensitivity and specificity. In addition to AHMM, Serfling models with 30% and 35% modification can be used to detect epidemics due to approximately the same accuracy but the simplicity of the calculations.

Several lineages of porcine epidemic diarrhea virus in Colombia during the 2014 and 2016 epidemic.

Porcine epidemic diarrhea virus (PEDV) is a significant global, enteric coronavirus in pigs and was first reported in Colombia in 2014. However, the epidemiology, genetic and antigenic characteristics of the virus have yet to be investigated. In this study, we investigated the dissemination of PEDV by testing 536 samples by RT-PCR over a 33-month period. The 35.8% of positive samples (n = 192) was significantly different (p < .01) between months over time, with a higher number of positives samples occurring at the beginning of the epidemic and during the second epidemic wave within the main pork producing region. The complete PEDV genomes were generated for 21 strains, which shared a high nucleotide and amino acid sequence identity, except for the spike (S) gene. Recombinant regions were identified within the Colombian strains and between Colombian and Asian PEDV strains. Phylogenetic analysis of the 21 Colombian strains demonstrated the presence of 7 lineages that shared common ancestors with PEDV strains from the United States. Moreover, the antigenic analysis demonstrated residue differences in the neutralizing epitopes in the spike and nucleocapsid proteins. Our results illustrated the simultaneous introduction of the two PEDV genotypes (GIIa American pandemic and S-INDEL) into the Colombian swine industry during the 2014 PEDV epidemic and enhanced our understanding of the epidemiology and molecular diversity of PEDV in Colombia.