Dynamic modeling can help insurers close the livestock protection gap

21.08.2020 148 views
Crops and livestock can face similar risks, but livestock is uniquely vulnerable to disease outbreaks that can inflict huge losses. Livestock diseases have a significant impact on the economies of different countries. Costs can come from both the direct expenses of culling infected animals and vaccination and the indirect costs of suspension of exports in the medium to long term. Economic losses come from disruption of the domestic market, loss of access to international markets, production and direct income losses, losses to related industries such as logistics, packing and supermarket and the financial, political and societal pressures of eradicating the diseases. According to a report, The economic impacts of foot and mouth disease—what are they, how big are they and where do they occur?, estimates indicate the economic impact of a foot-and-mouth disease outbreak can be as high as USD 11 billion globally. Historical outbreaks of the disease cost Taiwan EUR 5.4 billion (USD 5.76 billion) in 1997 and EUR 3.5 billion in the UK in 2001. The most effective tools to reduce the economic burden of livestock diseases are the establishment of disease control measures and the expansion of livestock insurance. China is the leading producer of chickens, pigs, goats, ducks and sheep and is the fourth-largest producer of cattle in the world by number of animals. China has improved its contingency plans and established controlled disease centers to reduce mortality event impacts. In addition, government support of livestock insurance in China has grown substantially since 2007, when premium subsidies for breeding sow in 22 provinces were offered, to expand across the country and offer subsidies for breeding sow, fattening pig, dairy cattle, yak and Tibetan sheep. Insurance policies cover animal mortality due to natural hazards, such as typhoon, tornado, wind, heavy rainfall, lightning, earthquake, hail, freeze, flood and snow; accidents, such as mudslide, landslide, fire, explosion, electric shock, drowning, wild animal attack, building collapse, and falling objects; dystocia; disease; and culling. Underinsured Risk Chinese livestock represents a significant underinsured risk in the global agriculture sector. Nationwide, the livestock premium volume of Yuan 10 billion (USD 1.4 billion) is about a quarter of the total agricultural premiums in China; however, the take-up for livestock insurance lags far behind that of crop insurance, resulting in a sizeable protection gap. Crops and livestock can face similar risks, as they may be affected by the same weather conditions. Livestock, however, is uniquely vulnerable to disease outbreaks that can inflict huge losses. For example, since the autumn of 2018, China has been hit by the African swine fever (ASF) virus. While ASF does not affect humans, for pigs it is highly contagious, with a high mortality rate and no treatment or vaccine. Before the outbreak of ASF, China had 400 million pigs—40% of the global total of one billion. Since the beginning of the ASF outbreak, China’s pig population has fallen 50%. While a disaster of this size would indicate loss ratios of 200% or greater for breeding sow and fattening pig policies, official statistics suggest many farmers have been reluctant to report and claim losses. Modeling is a powerful tool to enhance the ability of decision-makers to quantify their risks and develop preparedness plans for a disease outbreak. Mathematical models of livestock disease transmission simulate the spatiotemporal spread of livestock disease in a region of interest. These models can accommodate different pathogens that may transmit via direct or indirect contact, airborne transmission and sale yards, as these are the most common sources/routes of disease transmission. A disease spread model should include geospatial information, historical data and information on local farming practices. Geospatial information allows the disease spread model to handle complex interactions between zoonotic (animal) reservoirs; incorporate the movement of animals from one region to another; and account for cross-contamination across multiple livestock populations. The model should integrate the livestock economic life cycle to understand how outbreaks start in a given region and spread across localized animal habitats via interaction at the transit hubs, slaughter and packaging facilities. Historical data provides essential pieces of information that can provide a framework for the types, likelihood and severity of historical events that can be used to calibrate the model, improve model estimates, and validate results. Different farming practices across multiple regions should be considered, resulting in some areas with higher rates of spread and severity than others. A dynamic disease spread model can be designed in a way to simulate the transmission of a disease within each herd by considering the contact between herds/farms as a result of the transportation of a herd to and from a sale yard or exposure to pathogens through veterinarians, milk tanks and other disease-contaminated items. Modeling Results The results of the model can show how an animal goes from being susceptible to being exposed, then infectious and eventually to being recovered or dead. Disease spread control plans and quantification of their effectiveness can be added to the model to study their impact in reducing the transmission and the de-escalation of the situation. The main control strategies are active surveillance, vaccinations, movement restrictions and culls. A full understanding of the risk to livestock exposures incorporates rare and common disease events and the full range of accidents and deaths owing to natural and anthropogenic hazards. Characterizing these risks can inform regulators and insurers looking to offer appropriately rated livestock insurance, as well as prospective policyholders looking to better understand the risk landscape they face—ultimately helping to close the protection gap. Source - https://www.air-worldwide.com
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