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Application of the ARIMA Model to Predict Under-Reporting of New Cases of Hansen’s Disease during the COVID-19 Pandemic in a Municipality of the Amazon Region

Author

Listed:
  • Valéria Perim da Cunha

    (Graduate Program in Intellectual Property and Information Technology Transfer - PROFNIT, Federal University of Tocantins, Palmas 77001-090, TO, Brazil)

  • Glenda Michele Botelho

    (Graduate Program in Intellectual Property and Information Technology Transfer - PROFNIT, Federal University of Tocantins, Palmas 77001-090, TO, Brazil)

  • Ary Henrique Morais de Oliveira

    (Graduate Program in Intellectual Property and Information Technology Transfer - PROFNIT, Federal University of Tocantins, Palmas 77001-090, TO, Brazil)

  • Lorena Dias Monteiro

    (Medicine Course, State University of Tocantins, Palmas 77020-122, TO, Brazil)

  • David Gabriel de Barros Franco

    (Graduate Program in Digital Agroenergy (PPGADIGITAL), Federal University of Tocantins, Palmas 77001-090, TO, Brazil)

  • Rafael da Costa Silva

    (Computing Department, Federal University of São Carlos, São Carlos 13565-905, SP, Brazil)

Abstract

This work aimed to apply the ARIMA model to predict the under-reporting of new Hansen’s disease cases during the COVID-19 pandemic in Palmas, Tocantins, Brazil. This is an ecological time series study of Hansen’s disease indicators in the city of Palmas between 2001 and 2020 using the autoregressive integrated moving averages method. Data from the Notifiable Injuries Information System and population estimates from the Brazilian Institute of Geography and Statistics were collected. A total of 7035 new reported cases of Hansen’s disease were analyzed. The ARIMA model (4,0,3) presented the lowest values for the two tested information criteria and was the one that best fit the data, as AIC = 431.30 and BIC = 462.28, using a statistical significance level of 0.05 and showing the differences between the predicted values and those recorded in the notifications, indicating a large number of under-reporting of Hansen’s disease new cases during the period from April to December 2020. The ARIMA model reported that 177% of new cases of Hansen’s disease were not reported in Palmas during the period of the COVID-19 pandemic in 2020. This study shows the need for the municipal control program to undertake immediate actions in terms of actively searching for cases and reducing their hidden prevalence.

Suggested Citation

  • Valéria Perim da Cunha & Glenda Michele Botelho & Ary Henrique Morais de Oliveira & Lorena Dias Monteiro & David Gabriel de Barros Franco & Rafael da Costa Silva, 2021. "Application of the ARIMA Model to Predict Under-Reporting of New Cases of Hansen’s Disease during the COVID-19 Pandemic in a Municipality of the Amazon Region," IJERPH, MDPI, vol. 19(1), pages 1-12, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:415-:d:715166
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    References listed on IDEAS

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    2. Cheung, Yin-Wong & Lai, Kon S, 1995. "Lag Order and Critical Values of the Augmented Dickey-Fuller Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 277-280, July.
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