Mathematical model of the 2010 foot-and-mouth disease epidemic in Japan and evaluation of control measures

Research aimed at understanding transmission networks, representing a network of "who infected whom" for an infectious disease outbreak, have been actively conducted in recent years. Transmission network models incorporating epidemiological and genetic data are valuable for elucidating disease transmission pathways. In this study, we reconstructed the transmission network of the foot-and-mouth disease (FMD) epidemic in Japan in 2010, and explored farm-level risk factors associated with increased risk of secondary transmission. A published, systematic Bayesian transmission network model was applied to epidemiological data of 292 infected farms and whole genome sequence data of 104 of the infected farms. This model can make inferences for known infected farms even lacking genetic data. After estimating the consensus network, the accuracy of the network was examined by comparison with epidemiological data. Then, risk factors inferred to have been sources of secondary transmission were explored using zero-inflated Poisson regression model. As far as we are aware, this study represents the largest FMD outbreak transmission network to be published by such means combining epidemiological and genetic data. The consensus network reasonably generated the epidemiological links, which were estimated from the actual epidemiological investigation. Among 292 farms, 101 farms (35%) were inferred to have been the sources of secondary transmission, and amongst these farms, the median number of secondary cases was 2 (min:1-max:18) farms. The farm-type (small and large -sized pig farms), the number of days from onset to notification, and the number of susceptible farms within a 1-km radius were significantly associated with secondary transmission. Transmission network modelling enabled inference of the connections between infected farms during the FMD epidemic and identified important factors for controlling the risk of secondary transmission. This study demonstrated that the predominant susceptible species held on a farm, farm size, and animal density were associated with increased onwards transmission. K E Y W O R D S foot-and-mouth disease, Japan, secondary transmission, transmission network, zero-inflated Poisson model | 2075 HAYAMA et Al. S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section at the end of the article. How to cite this article: Hayama Y, Firestone SM, Stevenson MA, et al. Reconstructing a transmission network and identifying risk factors of secondary transmissions in the 2010 foot-and-mouth disease outbreak in Japan. Transbound Emerg

Section: Discussionsupporting

confidence: 82%

Reconstructing a transmission network and identifying risk factors of secondary transmissions in the 2010 foot‐and‐mouth disease outbreak in Japan

Hayama

Firestone

Stevenson

et al. 2019

“…For example, poliovirus is infective at pH values of 3.0, while FMDV is labile below pH values of 6.0 (Racaniello, 2013). Additionally, while both, poliovirus and FMDV have been shown to persist longer when the virus was inoculated onto a faecal media, and conditions in TA B L E 1 This table provides references by grouping for current models used for strategic policy development and studies that were either removed from further analysis or included for the full statistical analysis References Group # of Studies (Andel, 2018;Dórea, Nöremark, Widgren, & Frössling, 2017;East et al, 2016;Gale et al, 2015;Garner & Beckett, 2005;Harvey et al, 2007;Hayama, Yamamoto, Kobayashi, Muroga, & Tsutsui, 2013;Keeling et al, 2001;SANSON et al, 2011;Stevenson et al, 2013;Tildesley & Ryan, 2012;Traulsen, Rave, Teuffert, & Krieter, 2011) Current Policy Models - (Barlow, 1972;Barlow & Donaldson, 1973;Donaldson, 1972;Donaldson & Ferris, 1975) Removed 4 (Alexandersen et al, 2002;Bedson et al, 1927;Bøtner & Belsham, 2012;Donaldson et al, 1970;Eisner & McVicar, 1980;Grzitdnov, 1957;Hyslop, 1965;Kindiakov, 1960;McColl et al, 1995;Nauryzbaev, 1966;Olitsky et al, 1928;Pacheco et al, 2017;Rozov, 1966;Sellers & Parker, 1969;Shil'nikov, 1959;Wagener, 1928) Included 16…”

Section: The Influence Of Environmental Factors On Viral Survivalmentioning

confidence: 99%

Environmental persistence of foot‐and‐mouth disease virus applied to endemic regions

Mielke

Garabed

2019

The consequences of foot‐and‐mouth disease impact regional economies and food security through animal mortality and morbidity, trade restrictions and burdens to veterinary infrastructure. Despite efforts to control the disease, some regions, mostly in warmer climates, persistently report disease outbreaks. Consequently, it is necessary to understand how environmental factors influence transmission, of this economically devastating disease. Extensive research covers basic aetiology and transmission potential of livestock and livestock products for foot‐and‐mouth disease virus (FMDV), with a subset evaluating environmental survival. However, this subset, completed in the early to mid‐20th century in Northern Europe and the United States, is not easily generalized to today's endemic locations. This review uncovered 20 studies, to assess current knowledge and analyse the effects of environmental variables on FMDV survival, using a Cox proportional hazards (Coxph) model. However, the dataset is limited, for example pH was included in three studies and only five studies reported both relative humidity (RH) and temperature. After dropping pH from the analysis, our results suggest that temperature alone does not describe FMDV survival; instead, interactions between RH and temperature have broader impacts across various conditions. For instance, FMDV is expected to survive longer during the wet season (survival at day 50 is ~90% at 16°C and 86% RH) versus the dry season (survival at day 50 approaches 0% at 16°C and 37.5% RH) or comparatively in the UK versus the Southwestern United States. Additionally, survival on vegetation topped 70% on day 75 when conditions exceeded 20°C with high RH (86%), drastically higher than the survival on inanimate surfaces at the same temperature and RH (~0%). This is important in tropical regions, where high temperatures can persist throughout the year, but RH varies. Therefore, parameter estimates, for disease modelling and control in endemic areas, require environmental survival data from a wider range of conditions.

“…Previously, detailed models combined with high‐resolution disease data have been used to describe FMDV transmission. Transmission kernels, which estimated the probability of transmission based on the distance from an infected farm, have been estimated from spatial incidence data from outbreaks that occurred in 2001 in the Netherlands (Boender et al., ), UK (Chis Ster and Ferguson, ; Chis Ster et al., , ) and Uruguay (Chowell et al., ) and in 2010 in Japan (Hayama et al., ) (Fig. ).…”

Section: Resultsmentioning

confidence: 99%

“…). The widest kernel represented transmission in the Dutch outbreak (Boender et al., ), and the narrowest kernel represented transmission in the Japanese outbreak (Hayama et al., ). All three kernels that represented the UK outbreak are similar and demonstrate widths intermediate between the Dutch and Japanese kernels.…”

Section: Resultsmentioning

confidence: 99%

“…Transmission kernels. The function that scales transmission with distance was estimated for the Dutch 2001 Panasia O outbreak (orange) (Boender et al., ), the Uruguayan 2001 type A outbreak (black) (Chowell et al., ), the UK 2001 Panasia O outbreak (red, blue, and green) (Chis Ster and Ferguson, ; Chis Ster et al., , ) and the Japanese 2010 outbreak (Hayama et al., ). The kernels for the UK outbreak were estimated for before the February 23rd movement ban (‘pre’), after the February 23rd movement ban (‘post’) or for the entire epidemic (‘all’).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Data‐Driven Models of Foot‐and‐Mouth Disease Dynamics: A Review

Pomeroy

Bansal

Tildesley

et al. 2015

Summary Foot-and-mouth disease virus (FMDV) threatens animal health and leads to considerable economic losses worldwide. Progress towards minimizing both veterinary and financial impact of the disease will be made with targeted disease control policies. In order to move towards targeted control, specific targets and detailed control strategies must be defined. One approach for identifying targets is to use mathematical and simulation models quantified with accurate and fine-scale data to design and evaluate alternative control policies. Nevertheless, published models of FMDV vary in modeling techniques and resolution of data incorporated. In order to determine which models and data sources contain enough detail to represent realistic control policy alternatives, we performed a systematic literature review of all FMDV dynamical models that use host data, disease data, or both data types. For the purpose of evaluating modeling methodology, we classified models by control strategy represented, resolution of models and data, and location modeled. We found that modeling methodology has been well developed to the point where multiple methods are available to represent detailed and contact-specific transmission and targeted control. However, detailed host and disease data needed to quantify these models are only available from a few outbreaks. To address existing challenges in data collection, novel data sources should be considered and integrated into models of FMDV transmission and control. We suggest modeling multiple endemic areas to advance local control, global control, and better understand FMDV transmission dynamics. With incorporation of additional data, models can assist with both the design of targeted control and identification of transmission drivers across geographic boundaries.