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Insurance contract for epidemiological diseases spread

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This paper presents the use of actuarial modeling for the spread of epidemiological diseases. Study is done based on a developed actuarial model of SIR infection which describes the transfer dynamics in an insurance contract in a given population. At the initial stage, we satisfied key assumptions and observed that the rate of infection is positively related and the rate of recovery is negatively related to the level premium payment. Hence, we developed a MATLAB program to calculate the minimum adjusted level premium for a hospitalization plan. Furthermore, this study expanded the basic model to eliminate some problems such as the Vector-Host relationship due to unsatisfied assumptions for the real data. It is reasonable to expand the SIR model by including Vector-Host transfer dynamics to find out an actuarial model for Dengue fever. Accordingly the length of an epidemic season for Dengue over the sample period can be estimated. Results demonstrate no impact from Vector-Host in determining the level premium payment and reveal the possibility of introducing an insurance policy for the spread of Dengue fever in Sri Lanka. Further, as a result, difficulties to clearly identify seasonal patterns of other diseases may also be overcome. We suggest the SIRS infection model with delayed differential equations as an appropriate solution to define an actuarial model for a wide range of diseases.
Title: Insurance contract for epidemiological diseases spread
Description:
This paper presents the use of actuarial modeling for the spread of epidemiological diseases.
Study is done based on a developed actuarial model of SIR infection which describes the transfer dynamics in an insurance contract in a given population.
At the initial stage, we satisfied key assumptions and observed that the rate of infection is positively related and the rate of recovery is negatively related to the level premium payment.
Hence, we developed a MATLAB program to calculate the minimum adjusted level premium for a hospitalization plan.
Furthermore, this study expanded the basic model to eliminate some problems such as the Vector-Host relationship due to unsatisfied assumptions for the real data.
It is reasonable to expand the SIR model by including Vector-Host transfer dynamics to find out an actuarial model for Dengue fever.
Accordingly the length of an epidemic season for Dengue over the sample period can be estimated.
Results demonstrate no impact from Vector-Host in determining the level premium payment and reveal the possibility of introducing an insurance policy for the spread of Dengue fever in Sri Lanka.
Further, as a result, difficulties to clearly identify seasonal patterns of other diseases may also be overcome.
We suggest the SIRS infection model with delayed differential equations as an appropriate solution to define an actuarial model for a wide range of diseases.

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