Dataset Information

Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas.

ABSTRACT: COVID-19, the first pandemic of this decade and the second in less than 15 years, has harshly taught us that viral diseases do not recognize boundaries; however, they truly do discriminate between aggressive and mediocre containment responses. We present a simple epidemiological model that is amenable to implementation in Excel spreadsheets and sufficiently accurate to reproduce observed data on the evolution of the COVID-19 pandemics in different regions [i.e., New York City (NYC), South Korea, Mexico City]. We show that the model can be adapted to closely follow the evolution of COVID-19 in any large city by simply adjusting parameters related to demographic conditions and aggressiveness of the response from a society/government to epidemics. Moreover, we show that this simple epidemiological simulator can be used to assess the efficacy of the response of a government/society to an outbreak. The simplicity and accuracy of this model will greatly contribute to democratizing the availability of knowledge in societies regarding the extent of an epidemic event and the efficacy of a governmental response.

SUBMITTER: Alvarez MM

PROVIDER: S-EPMC7900250 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas.

Alvarez Mario Moisés MM González-González Everardo E Trujillo-de Santiago Grissel G

Scientific reports 20210222 1

COVID-19, the first pandemic of this decade and the second in less than 15 years, has harshly taught us that viral diseases do not recognize boundaries; however, they truly do discriminate between aggressive and mediocre containment responses. We present a simple epidemiological model that is amenable to implementation in Excel spreadsheets and sufficiently accurate to reproduce observed data on the evolution of the COVID-19 pandemics in different regions [i.e., New York City (NYC), South Korea, ...[more]

PMID: 33619337

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Project description:African swine fever (ASF) and classical swine fever (CSF) are two major transboundary animal diseases of swine with important socioeconomic consequences at farm, subnational and national level. The objective of this study was to evaluate the direct cost of outbreaks and their control at country/regional level in four countries: namely CSF in Colombia in 2015-2016, the retrospective cost of ASF in the Philippines in 2019 and in a province of Vietnam in 2020 and a hypothetical ASF scenario in one region in North Macedonia, using the newly developed Outbreak Costing Tool (OutCosT). The tool calculates the costs of 106 different items, broken down by up to four types of farms, and by who assumes the cost (whether veterinary services, farmers or other stakeholders). The total cost of CSF in Colombia was US$ 3.8 million, of which 88% represented the cost of the vaccination campaign. For ASF, there were wide differences between countries: US$ 8,26,911 in Lao Cai (Vietnam), US$ 33,19,666 in North Macedonia and over US$ 58 million in the Philippines. While in the Philippines and Vietnam, 96-98% of the cost occurred in the affected farms, the highest expenditure in North Macedonia scenario was the movement control of the neighbouring and at-risk farms (77%). These important differences between countries depend on the spread of the disease, but also on the production systems affected and the measures applied. Apart from the financial cost, these diseases have other negative impacts, especially in the livelihoods of smallholder farms. The OutCosT tool also allows users to evaluate qualitatively other important aspects related to the epidemics, such as the impact on human health, the environment, animal welfare, socioeconomic vulnerability, trading and political response. OutCosT, which is a FAO corporate tool (available online at: https://www.fao.org/fileadmin/user_upload/faoweb/animal-health/OutCosT_PIG.xlsx), can be an important tool to support country authorities to rapidly respond to a swine disease outbreak by estimating the associated costs and for advocacy purposes to mobilize resources at national or international levels.

Dataset Information

Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas.

Publications

Modeling COVID-19 epidemics in an Excel spreadsheet to enable first-hand accurate predictions of the pandemic evolution in urban areas.

Similar Datasets

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