Literature DB >> 33900929

Age-Stratified Infection Probabilities Combined With a Quarantine-Modified Model for COVID-19 Needs Assessments: Model Development Study.

Vena Pearl Bongolan1, Jose Marie Antonio Minoza1, Romulo de Castro2, Jesus Emmanuel Sevilleja3.   

Abstract

BACKGROUND: Classic compartmental models such as the susceptible-exposed-infectious-removed (SEIR) model all have the weakness of assuming a homogenous population, where everyone has an equal chance of getting infected and dying. Since it was identified in Hubei, China, in December 2019, COVID-19 has rapidly spread around the world and been declared a pandemic. Based on data from Hubei, infection and death distributions vary with age. To control the spread of the disease, various preventive and control measures such as community quarantine and social distancing have been widely used.
OBJECTIVE: Our aim is to develop a model where age is a factor, considering the study area's age stratification. Additionally, we want to account for the effects of quarantine on the SEIR model.
METHODS: We use the age-stratified COVID-19 infection and death distributions from Hubei, China (more than 44,672 infections as of February 11, 2020) as an estimate or proxy for a study area's infection and mortality probabilities for each age group. We then apply these probabilities to the actual age-stratified population of Quezon City, Philippines, to predict infectious individuals and deaths at peak. Testing with different countries shows the predicted number of infectious individuals skewing with the country's median age and age stratification, as expected. We added a Q parameter to the SEIR model to include the effects of quarantine (Q-SEIR).
RESULTS: The projections from the age-stratified probabilities give much lower predicted incidences of infection than the Q-SEIR model. As expected, quarantine tends to delay the peaks for both the exposed and infectious groups, and to "flatten" the curve or lower the predicted values for each compartment. These two estimates were used as a range to inform the local government's planning and response to the COVID-19 threat.
CONCLUSIONS: Age stratification combined with a quarantine-modified model has good qualitative agreement with observations on infections and death rates. That younger populations will have lower death rates due to COVID-19 is a fair expectation for a disease where most fatalities are among older adults. ©Vena Pearl Bongolan, Jose Marie Antonio Minoza, Romulo de Castro, Jesus Emmanuel Sevilleja. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.05.2021.

Entities:  

Keywords:  COVID-19; SEIR; age stratification theory; epidemic modeling; infection probability; mathematical modelling

Year:  2021        PMID: 33900929     DOI: 10.2196/19544

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   5.428


  3 in total

1.  Modeling the initial phase of COVID-19 epidemic: The role of age and disease severity in the Basque Country, Spain.

Authors:  Akhil Kumar Srivasrav; Nico Stollenwerk; Joseba Bidaurrazaga Van-Dierdonck; Javier Mar; Oliver Ibarrondo; Maíra Aguiar
Journal:  PLoS One       Date:  2022-07-13       Impact factor: 3.752

2.  Using machine learning to create a decision tree model to predict outcomes of COVID-19 cases in the Philippines.

Authors:  Julius R Migriño; Ani Regina U Batangan
Journal:  Western Pac Surveill Response J       Date:  2021-09-14

3.  Prediction of COVID-19 Data Using Hybrid Modeling Approaches.

Authors:  Weiping Zhao; Yunpeng Sun; Ying Li; Weimin Guan
Journal:  Front Public Health       Date:  2022-07-22
  3 in total

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