COVID-19 and the flu: data simulations and computational modelling to guide public health strategies
| Autor: | Verda Tunaligil, Sıddıka Semahat Demir, Mehmet Canbulat, Gulsen Meral, Mustafa Resat Dabak |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
COVID-19 Vaccines Epidemiology Pneumonia Viral coronavirus Global Health Disease Outbreaks Scientific evidence Multidisciplinary approach Influenza Human Pandemic Global health Humans Medicine Computer Simulation AcademicSubjects/MED00780 Pandemics Actuarial science Artificial learning business.industry SARS-CoV-2 Social distance Public health social distancing COVID-19 International health Planning Techniques vaccination Incentive Influenza Vaccines Communicable Disease Control Public Health Practice Family Practice business influenza |
| Zdroj: | Family Practice |
| ISSN: | 1460-2229 0263-2136 |
| Popis: | Background Pandemics threaten lives and economies. This article addresses the global threat of the anticipated overlap of COVID-19 with seasonal-influenza. Objectives Scientific evidence based on simulation methodology is presented to reveal the impact of a dual outbreak, with scenarios intended for propagation analysis. This article aims at researchers, clinicians of family medicine, general practice and policy-makers worldwide. The implications for the clinical practice of primary health care are discussed. Current research is an effort to explore new directions in epidemiology and health services delivery. Methods Projections consisted of machine learning, dynamic modelling algorithms and whole simulations. Input data consisted of global indicators of infectious diseases. Four simulations were run for ‘20% versus 60% flu-vaccinated populations’ and ‘10 versus 20 personal contacts’. Outputs consisted of numerical values and mathematical graphs. Outputs consisted of numbers for ‘never infected’, ‘vaccinated’, ‘infected/recovered’, ‘symptomatic/asymptomatic’ and ‘deceased’ individuals. Peaks, percentages, R0, durations are reported. Results The best-case scenario was one with a higher flu-vaccination rate and fewer contacts. The reverse generated the worst outcomes, likely to disrupt the provision of vital community services. Both measures were proven effective; however, results demonstrated that ‘increasing flu-vaccination rates’ is a more powerful strategy than ‘limiting social contacts’. Conclusions Results support two affordable preventive measures: (i) to globally increase influenza-vaccination rates, (ii) to limit the number of personal contacts during outbreaks. The authors endorse changing practices and research incentives towards multidisciplinary collaborations. The urgency of the situation is a call for international health policy to promote interdisciplinary modern technologies in public health engineering. |
| Databáze: | OpenAIRE |
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