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Modeling Ivory Coast COVID-19 cases: Identification of a high-performance model for utilization.

ABSTRACT: This study modelled the reported daily cumulative confirmed, discharged and death Coronavirus disease 2019 (COVID-19) cases using six econometric models in simple, quadratic, cubic and quartic forms and an autoregressive integrated moving average (ARIMA) model. The models were compared employing R-squared and Root Mean Square Error (RMSE). The best model was used to forecast confirmed, discharged and death COVID-19 cases for October 2020 to February 2021. The predicted number of confirmed and death COVID-19 cases are alarming. Good planning and innovative approaches are required to prevent the forecasted alarming infection and death in Ivory Coast. The applications of findings of this study will ensure that the COVID-19 does not crush the Ivory Coast's health, economic, social and political systems.

SUBMITTER: Nwosu UI

PROVIDER: S-EPMC7837195 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Modeling Ivory Coast COVID-19 cases: Identification of a high-performance model for utilization.

Nwosu Ugochinyere Ihuoma UI Obite Chukwudi Paul CP

Results in physics 20201224

This study modelled the reported daily cumulative confirmed, discharged and death Coronavirus disease 2019 (COVID-19) cases using six econometric models in simple, quadratic, cubic and quartic forms and an autoregressive integrated moving average (ARIMA) model. The models were compared employing R-squared and Root Mean Square Error (RMSE). The best model was used to forecast confirmed, discharged and death COVID-19 cases for October 2020 to February 2021. The predicted number of confirmed and de ...[more]

PMID: 33520627

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Project description:Unemployment rates in the United States are rapidly increasing as a result of the COVID-19 pandemic and attendant economic disruption. As employees lose their jobs, many will lose their employer-sponsored dental insurance (ESDI). Changes in insurance coverage are directly related to the oral health of the population, with many at risk of losing access to dental care. We assessed the impact of recent unemployment rates on insurance coverage and dental utilization. We estimated changes in dental insurance coverage at the state level, using previously applied econometric estimates. Expected changes in types of dental procedures performed at dental practices nationwide were assessed using a microsimulation model, using national practice survey data. Changes in emergency department (ED) visits for dental problems were estimated by fitting trendlines to ED visit patterns by payer type. Sensitivity analyses were conducted to assess how variations in unemployment rates and rates of ESDI in response to unemployment could alter the results. Since March 2020, the national unemployment rate has increased by 8.40 percentage points, an increase expected to result in more than 16 million individuals losing ESDI in the United States. Of these individuals, 45.0% are likely to enroll in their state's Medicaid and Children's Health Insurance Program, and 47.0% are expected to become uninsured. With these expected changes in dental insurance coverage, the average dental practice would experience decreases in routine checkup visits but increases in tooth extraction, a procedure that is highly used by publicly insured or uninsured patients. In addition, dental-related ED visits would be expected to grow by 4.0%. Losses of employment caused by the COVID-19 in the United States can have countervailing effects on people's health by impeding access to dental care. Lack of dental insurance is expected to be more pronounced in states that have not expanded Medicaid or do not provide Medicaid dental benefits for adults.

Dataset Information

Modeling Ivory Coast COVID-19 cases: Identification of a high-performance model for utilization.

Publications

Modeling Ivory Coast COVID-19 cases: Identification of a high-performance model for utilization.

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