Dataset Information

Improving mariculture insurance premium rate calculation using an information diffusion model.

ABSTRACT: Mariculture is a well-known high-risk industry. However, mariculture insurance, which is an important risk management tool, is facing serious market failure. An important reason for this market failure lies in the unsound premium rate and pricing method. Due to a lack of long-term yield data, empirical rates are often adopted, but this adoption can lead to a high loss ratio. This paper provides an improved method for premium computation of mariculture insurance using an information diffusion model (IDM). An example of oyster insurance in China shows that, compared with the traditional pricing approach, the IDM can greatly improve the accuracy and stability of premium rate calculations, especially in cases of small samples.

SUBMITTER: Zhang Q

PROVIDER: S-EPMC8700043 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Improving mariculture insurance premium rate calculation using an information diffusion model.

Zhang Qian Q

PloS one 20211223 12

Mariculture is a well-known high-risk industry. However, mariculture insurance, which is an important risk management tool, is facing serious market failure. An important reason for this market failure lies in the unsound premium rate and pricing method. Due to a lack of long-term yield data, empirical rates are often adopted, but this adoption can lead to a high loss ratio. This paper provides an improved method for premium computation of mariculture insurance using an information diffusion mod ...[more]

PMID: 34941908

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Project description:BackgroundThe performance of previously published glomerular filtration rate (GFR) estimation equations degrades when directly used in Chinese population. We incorporated more independent variables and using complicated non-linear modeling technology (artificial neural network, ANN) to develop a more accurate GFR estimation model for Chinese population.MethodsThe enrolled participants came from the Third Affiliated Hospital of Sun Yat-sen University, China from Jan 2012 to Jun 2016. Participants with age < 18, unstable kidney function, taking trimethoprim or cimetidine, or receiving dialysis were excluded. Among the finally enrolled 1952 participants, 1075 participants (55.07%) from Jan 2012 to Dec 2014 were assigned as the development data whereas 877 participants (44.93%) from Jan 2015 to Jun 2016 as the internal validation data. We in total developed 3 GFR estimation models: a 4-variable revised CKD-EPI (chronic kidney disease epidemiology collaboration) equation (standardized serum creatinine and cystatin C, age and gender), a 9-variable revised CKD-EPI equation (additional auxiliary variables: body mass index, blood urea nitrogen, albumin, uric acid and hemoglobin), and a 9-variable ANN model.ResultsCompared with the 4-variable equation, the 9-variable equation could not achieve superior performance in the internal validation data (mean of difference: 5.00 [3.82, 6.54] vs 4.67 [3.55, 5.90], P = 0.5; interquartile range (IQR) of difference: 18.91 [17.43, 20.48] vs 20.11 [18.46, 21.80], P = 0.05; P30: 76.6% [73.7%, 79.5%] vs 75.8% [72.9%, 78.6%], P = 0.4), but the 9-variable ANN model significantly improve bias and P30 accuracy (mean of difference: 2.77 [1.82, 4.10], P = 0.007; IQR: 19.33 [17.77, 21.17], P = 0.3; P30: 80.0% [77.4%, 82.7%], P < 0.001).ConclusionsIt is suggested that using complicated non-linear models like ANN could fully utilize the predictive ability of the independent variables, and then finally achieve a superior GFR estimation model.

Project description:ObjectiveThe Affordable Care Act allows insurers to charge up to 50% higher premiums to tobacco users, making tobacco use the only behavioral factor that can be used to rate premiums in the nongroup insurance market. Some states have set more restrictive limits on rating for tobacco use, and several states have outlawed tobacco premium surcharges altogether. We examined the impact of state level tobacco surcharge policy on health insurance enrollment decisions among smokers.Study designWe compared insurance enrollment in states that did and did not allow tobacco surcharges, using a difference-in-difference approach to compare the policy effects among smokers and nonsmokers. We also used geographic variation in tobacco surcharges to examine how the size of the surcharge affects insurance coverage, again comparing smokers to nonsmokers.Data collectionWe linked data from two components of the Current Population Survey-the 2015 and 2019 Annual Social and Economic Supplement and the Tobacco Use Supplement, which we combined with data on marketplace plan premiums. We also collected qualitative data from a survey of smokers who did not have insurance through an employer or public program.Principal findingsAllowing a tobacco surcharge reduced insurance enrollment among smokers by 4.0 percentage points (P = .01). Further, smokers without insurance through an employer or public program were 9.0 percentage points less likely (P < .01) to enroll in a nongroup plan if they were subject to a tobacco surcharge. In states with surcharges, enrollment among smokers was 3.4 percentage points lower (P < .01) for every 10 percentage point increase in the tobacco surcharge.ConclusionsTobacco use is the largest cause of preventable illness in the United States. State tobacco surcharge policy may have a substantial impact on whether tobacco users choose to remain insured and consequently their ability to receive care critical for preventing and treating tobacco-related disease.

Dataset Information

Improving mariculture insurance premium rate calculation using an information diffusion model.

Publications

Improving mariculture insurance premium rate calculation using an information diffusion model.

Similar Datasets

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