A method to assess COVID-19 infected numbers in Italy during peak pandemic period

Tradigo, Giuseppe; Guzzi, Pietro Hiram; Kahveci, Tamer; Veltri, Pierangelo

doi:10.1109/bibm49941.2020.9313291

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…Simulating the spread of COVID-19 has the potential to mitigate such challenges, help to better manage the healthcare system, and provide guidance to policy-makers on the effectiveness of various (current, planned, or discussed) mitigation measures. To this end, many COVID-19 simulation models are proposed (6)(7)(8)(9)(10), some of which are announced to assist in decision-making for policy-makers in countries such as the United Kingdom [ICL (9)], United States [IHME (10)], and Switzerland [IBZ (11)].…”

Section: Introductionmentioning

confidence: 99%

COVIDHunter: COVID-19 Pandemic Wave Prediction and Mitigation via Seasonality Aware Modeling

Alser

Kim

Alserr

et al. 2022

Front. Public Health

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Early detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID-19 tests performed in every country, simulating the COVID-19 spread along with the potential effect of each mitigation strategy currently remains one of the most effective ways in managing the healthcare system and guiding policy-makers. We introduce COVIDHunter, a flexible and accurate COVID-19 outbreak simulation model that evaluates the current mitigation measures that are applied to a region, predicts COVID-19 statistics (the daily number of cases, hospitalizations, and deaths), and provides suggestions on what strength the upcoming mitigation measure should be. The key idea of COVIDHunter is to quantify the spread of COVID-19 in a geographical region by simulating the average number of new infections caused by an infected person considering the effect of external factors, such as environmental conditions (e.g., climate, temperature, humidity), different variants of concern, vaccination rate, and mitigation measures. Using Switzerland as a case study, COVIDHunter estimates that we are experiencing a deadly new wave that will peak on 26 January 2022, which is very similar in numbers to the wave we had in February 2020. The policy-makers have only one choice that is to increase the strength of the currently applied mitigation measures for 30 days. Unlike existing models, the COVIDHunter model accurately monitors and predicts the daily number of cases, hospitalizations, and deaths due to COVID-19. Our model is flexible to configure and simple to modify for modeling different scenarios under different environmental conditions and mitigation measures. We release the source code of the COVIDHunter implementation at https://github.com/CMU-SAFARI/COVIDHunter and show how to flexibly configure our model for any scenario and easily extend it for different measures and conditions than we account for.

show abstract

Section: Introductionmentioning

confidence: 99%

COVIDHunter: COVID-19 Pandemic Wave Prediction and Mitigation via Seasonality Aware Modeling

Alser

Kim

Alserr

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

show abstract

“…Simulating the spread of COVID-19 has the potential to mitigate the effects of the three key issues, help to better manage the healthcare system, and provide guidance to policy-makers on the effectiveness of various (current, planned or discussed) social distancing and mitigation measures. To this end, many COVID-19 simulation models are proposed (e.g., (Tradigo et al, 2020;Russell et al, 2020;Ashcroft et al, 2020)), some of which are announced to assist in decision-making for policymakers in countries such as the United Kingdom (ICL (Flaxman et al, 2020)), United States (IHME (Reiner et al, 2020)), and Switzerland (IBZ (Huisman et al, 2020)). These models tend to follow one of two key approaches.…”

Section: Introductionmentioning

confidence: 99%

COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model

Alser¹,

Kim²,

Alserr³

et al. 2021

Preprint

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Motivation:Early detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID-19 tests performed in every country, simulating the COVID-19 spread along with the potential effect of each mitigation strategy currently remains one of the most effective ways in managing the healthcare system and guiding policy-makers. We introduce COVIDHunter, a flexible and accurate COVID-19 outbreak simulation model that evaluates the current mitigation measures that are applied to a region and provides suggestions on what strength the upcoming mitigation measure should be. The key idea of COVIDHunter is to quantify the spread of COVID-19 in a geographical region by simulating the average number of new infections caused by an infected person considering the effect of external factors, such as environmental conditions (e.g., climate, temperature, humidity) and mitigation measures. Results: Using Switzerland as a case study, COVIDHunter estimates that the policy-makers need to keep the current mitigation measures for at least 30 days to prevent demand from quickly exceeding existing hospital capacity. Relaxing the mitigation measures by 50% for 30 days increases both the daily capacity need for hospital beds and daily number of deaths exponentially by an average of 23.8×, who may occupy ICU beds and ventilators for a period of time. Unlike existing models, the COVIDHunter model accurately monitors and predicts the daily number of cases, hospitalizations, and deaths due to COVID-19. Our model is flexible to configure and simple to modify for modeling different scenarios under different environmental conditions and mitigation measures.

show abstract

COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model

Alser

Kim

Alserr

et al. 2021

Preprint

View full text Add to dashboard Cite

Motivation: Early detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID- 19 tests performed in every country, simulating the COVID-19 spread along with the potential effect of each mitigation strategy currently remains one of the most effective ways in managing the healthcare system and guiding policy-makers. We introduce COVIDHunter, a flexible and accurate COVID-19 outbreak simulation model that evaluates the current mitigation measures that are applied to a region and provides suggestions on what strength the upcoming mitigation measure should be. The key idea of COVIDHunter is to quantify the spread of COVID-19 in a geographical region by simulating the average number of new infections caused by an infected person considering the effect of external factors, such as environmental conditions (e.g., climate, temperature, humidity) and mitigation measures. Results: Using Switzerland as a case study, COVIDHunter estimates that the policy-makers need to keep the current mitigation measures for at least 30 days to prevent demand from quickly exceeding existing hospital capacity. Relaxing the mitigation measures by 50% for 30 days increases both the daily capacity need for hospital beds and daily number of deaths exponentially by an average of 23.8x, who may occupy ICU beds and ventilators for a period of time. Unlike existing models, the COVIDHunter model accurately monitors and predicts the daily number of cases, hospitalizations, and deaths due to COVID-19. Our model is flexible to configure and simple to modify for modeling different scenarios under different environmental conditions and mitigation measures. Availability: https://github.com/CMU-SAFARI/COVIDHunter

show abstract

A method to assess COVID-19 infected numbers in Italy during peak pandemic period

Cited by 6 publications

References 14 publications

COVIDHunter: COVID-19 Pandemic Wave Prediction and Mitigation via Seasonality Aware Modeling

COVIDHunter: COVID-19 Pandemic Wave Prediction and Mitigation via Seasonality Aware Modeling

COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model

COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model

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