Challenges and opportunities for using national animal datasets to support foot-and-mouth disease control

Designing one-step reverse transcriptase loop-mediated isothermal amplification for serotype O foot-and-mouth disease virus detection during the 2022 outbreak in East Java, Indonesia

Background and Aim

Various methods can detect foot-and-mouth disease (FMD) in cows, but they necessitate resources, time, costs, laboratory facilities, and specific clinical specimen submission, often leading to FMD virus (FMDV) diagnosis delays. The 2022 FMD outbreak in East Java, Indonesia, highlighted the need for an easy, inexpensive, rapid, and accurate detection approach. This study aims to devise a one-step reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) technique and phylogenetic analysis to detect the serotype O FMDV outbreak in East Java.

Materials and Methods

Swab samples were collected from the foot vesicles, nasal secretions, and saliva of five suspected FMDV-infected cows in East Java between June and July 2022. The RT-LAMP design used hydroxy naphthol blue dye or SYBR Green I dye, with confirmatory analysis through reverse transcriptase polymerase chain reaction (RT-PCR) targeting 249 base pairs. PCR products underwent purification, sequencing, and nucleotide alignment, followed by phylogenetic analysis.

Results

The RT-LAMP method using hydroxy naphthol blue dye displayed a positive reaction through a color shift from purple to blue in the tube. Naked-eye observation in standard light or ultraviolet (UV) light at 365 nm, with SYBR Green I stain, also revealed color change. Specifically, using SYBR Green I dye, UV light at 365 nm revealed a color shift from yellow to green, signifying a positive reaction. Nucleotide alignment revealed mutations and deletion at the 15th sequence in the JT-INDO-K3 isolate from the East Java FMDV outbreak. Despite differing branches, the phylogenetic tree placed it in the same cluster as serotype O FMDV from Malaysia and Mongolia.

Conclusion

JT-INDO-K3 exhibited distinctions from Indonesian serotype O FMDV isolates and those documented in GenBank. Then, the RT-LAMP method used in this study has a detection limit 10 times higher latter than the conventional RT-PCR limit, without any cross-reactivity among strains.

Analysis of cattle movement networks in Paraguay: Implications for the spread and control of infectious diseases

Beef exports represent a substantial part of Paraguay's agricultural sector. Cattle movements involve a high risk due to the possible spread of bovine diseases that can have a significant impact on the country's economy. We analyzed cattle movements from 2014 to 2018 using the networks analysis methodology at the holding and district levels at different temporal scales. We built two types of networks to identify network characteristics that may contribute to the spread of two diseases with different epidemiological characteristics: i) a network including all cattle movements to consider the transmission of a disease of rapid spread like foot and mouth disease, and ii) a network including only cow movements to account for bovine brucellosis, a disease of slow spread that occurs mainly in adult females. Network indicators did not vary substantially among the cattle and cow only networks. The holdings/districts included in the largest strongly connected components were distributed throughout the country. Percolation analysis performed at the holding level showed that a large number of holdings should be removed to make the largest strongly connected component disappear. Higher values of the centrality indicators were found for markets than for farms, indicating that they may play an important role in the spread of an infectious disease. At the holding level (but not at the district level), the networks exhibited characteristics of small-world networks. This property may facilitate the spread of foot and mouth disease in case of re-emergence, or of bovine brucellosis in the country through cattle movements. They should be taken into account when implementing surveillance or control measures for these diseases.

Phylodynamic analysis of the highly pathogenic avian influenza H5N8 epidemic in France, 2016-2017

In 2016-2017, France experienced a devastating epidemic of highly pathogenic avian influenza (HPAI) H5N8, with more than 400 outbreaks reported in poultry farms. We analyzed the spatiotemporal dynamics of the epidemic using a structured-coalescent-based phylodynamic approach that combined viral genomic data (n = 196; one viral genome per farm) and epidemiological data. In the process, we estimated viral migration rates between départements (French administrative regions) and the temporal dynamics of the effective viral population size (Ne) in each département. Viral migration rates quantify viral spread between départements and Ne is a population genetic measure of the epidemic size and, in turn, is indicative of the within-département transmission intensity. We extended the phylodynamic analysis with a generalized linear model to assess the impact of multiple factors-including large-scale preventive culling and live-duck movement bans-on viral migration rates and Ne. We showed that the large-scale culling of ducks that was initiated on 4 January 2017 significantly reduced the viral spread between départements. No relationship was found between the viral spread and duck movements between départements. The within-département transmission intensity was found to be weakly associated with the intensity of duck movements within départements. Together, these results indicated that the virus spread in short distances, either between adjacent départements or within départements. Results also suggested that the restrictions on duck transport within départements might not have stopped the viral spread completely. Overall, we demonstrated the usefulness of phylodynamics in characterizing the dynamics of a HPAI epidemic and assessing control measures. This method can be adapted to investigate other epidemics of fast-evolving livestock pathogens.

Cattle transport network predicts endemic and epidemic foot-and-mouth disease risk on farms in Turkey

The structure of contact networks affects the likelihood of disease spread at the population scale and the risk of infection at any given node. Though this has been well characterized for both theoretical and empirical networks for the spread of epidemics on completely susceptible networks, the long-term impact of network structure on risk of infection with an endemic pathogen, where nodes can be infected more than once, has been less well characterized. Here, we analyze detailed records of the transportation of cattle among farms in Turkey to characterize the global and local attributes of the directed—weighted shipments network between 2007-2012. We then study the correlations between network properties and the likelihood of infection with, or exposure to, foot-and-mouth disease (FMD) over the same time period using recorded outbreaks. The shipments network shows a complex combination of features (local and global) that have not been previously reported in other networks of shipments; i.e. small-worldness, scale-freeness, modular structure, among others. We find that nodes that were either infected or at high risk of infection with FMD (within one link from an infected farm) had disproportionately higher degree, were more central (eigenvector centrality and coreness), and were more likely to be net recipients of shipments compared to those that were always more than 2 links away from an infected farm. High in-degree (i.e. many shipments received) was the best univariate predictor of infection. Low in-coreness (i.e. peripheral nodes) was the best univariate predictor of nodes always more than 2 links away from an infected farm. These results are robust across the three different serotypes of FMD observed in Turkey and during periods of low-endemic prevalence and high-prevalence outbreaks.

Contact network epidemiology has been extensively used in the context of infectious diseases, primarily focusing on epidemic diseases. In this paper we use detailed recorded data about cattle exchange between farms in Turkey from 2007 to 2012, to build, analyze and characterize the directed-weighted complex network of shipments of cattle. Additionally, using outbreaks data about recorded cases of foot-and-mouth disease (FMD) in Turkey, we assess the correlation between the “farm’s” position in the network (importance) and the risk of being infected with FMD, which has been endemic in Turkey for a long time. We find some network measures that are more likely to identify high-risk and low-risk farms (in-degree and in-coreness, respectively) when proposing strategies for surveillance or containment of an infectious disease.