scholarly journals Optimal control of the COVID-19 pandemic: controlled sanitary deconfinement in Portugal

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Cristiana J. Silva ◽  
Carla Cruz ◽  
Delfim F. M. Torres ◽  
Alberto P. Muñuzuri ◽  
Alejandro Carballosa ◽  
...  
Keyword(s):  
Public Health ◽  
Optimal Control ◽  
Deterministic Model ◽  
Decision Support Tool ◽  
Discrete Version ◽  
Protection Measures ◽  
Policy Makers ◽  
Support Tool ◽  
Public Health Decision ◽  
Health Decision

AbstractThe COVID-19 pandemic has forced policy makers to decree urgent confinements to stop a rapid and massive contagion. However, after that stage, societies are being forced to find an equilibrium between the need to reduce contagion rates and the need to reopen their economies. The experience hitherto lived has provided data on the evolution of the pandemic, in particular the population dynamics as a result of the public health measures enacted. This allows the formulation of forecasting mathematical models to anticipate the consequences of political decisions. Here we propose a model to do so and apply it to the case of Portugal. With a mathematical deterministic model, described by a system of ordinary differential equations, we fit the real evolution of COVID-19 in this country. After identification of the population readiness to follow social restrictions, by analyzing the social media, we incorporate this effect in a version of the model that allow us to check different scenarios. This is realized by considering a Monte Carlo discrete version of the previous model coupled via a complex network. Then, we apply optimal control theory to maximize the number of people returning to “normal life” and minimizing the number of active infected individuals with minimal economical costs while warranting a low level of hospitalizations. This work allows testing various scenarios of pandemic management (closure of sectors of the economy, partial/total compliance with protection measures by citizens, number of beds in intensive care units, etc.), ensuring the responsiveness of the health system, thus being a public health decision support tool.

A Multicriteria Spatiotemporal System for Influenza Epidemic Surveillance

2021 ◽  
pp. 452-479
Author(s):  
Fatima-Zohra Younsi ◽  
Djamila Hamdadou ◽  
Salem Chakhar
Keyword(s):  
Public Health ◽  
High Risk ◽  
Seasonal Influenza ◽  
Control Strategies ◽  
Ranking Method ◽  
Influenza Surveillance ◽  
Policy Makers ◽  
Promethee Ii ◽  
Public Health Decision ◽  
Health Decision

Influenza has been a growing concern for the public health decision makers/policy makers. Indeed, they are in need of a real geo-making tool for monitoring and surveillance. The chapter aims to introduce a novel spatiotemporal decision system based on multicriteria ranking method, information geographic system (GIS), and SEIRSW system for public health. The later was designed, implemented, and validated in previous research for influenza risk assessment. The authors highlight the use of PROMETHEE II ranking method of multi-criteria decision analysis in GIS that incorporates various factors to monitor and identify potential high-risk areas of seasonal influenza and disease mapping. Factors related to the risk of seasonal influenza are obtained from simulation system and constitute the input values of PROMETHEE II ranking method for the 26 communes of the city of Oran, Algeria. The proposed system has demonstrated analytical capabilities in targeting high-risk spots and influenza surveillance monitoring system and it can help public health policy makers prioritize in their response goals and evaluate control strategies.

scholarly journals Integrated vaccination and non-pharmaceutical interventions based strategies in Ontario, Canada, as a case study: a mathematical modelling study

2021 ◽  
Vol 18 (180) ◽  
pp. 20210009
Author(s):  
Matthew Betti ◽  
Nicola Luigi Bragazzi ◽  
Jane M. Heffernan ◽  
Jude Kong ◽  
Angie Raad
Keyword(s):  
Public Health ◽  
Control Measures ◽  
Policy Makers ◽  
Local Public Health ◽  
Public Health Decision ◽  
The Public ◽  
Epidemiological Trend ◽  
Health Decision ◽  
Pharmaceutical Interventions

Recently, two coronavirus disease 2019 (COVID-19) vaccine products have been authorized in Canada. It is of crucial importance to model an integrated/combined package of non-pharmaceutical (physical/social distancing) and pharmaceutical (immunization) public health control measures. A modified epidemiological, compartmental SIR model was used and fit to the cumulative COVID-19 case data for the province of Ontario, Canada, from 8 September 2020 to 8 December 2020. Different vaccine roll-out strategies were simulated until 75% of the population was vaccinated, including a no-vaccination scenario. We compete these vaccination strategies with relaxation of non-pharmaceutical interventions. Non-pharmaceutical interventions were supposed to remain enforced and began to be relaxed on 31 January, 31 March or 1 May 2021. Based on projections from the data and long-term extrapolation of scenarios, relaxing the public health measures implemented by re-opening too early would cause any benefits of vaccination to be lost by increasing case numbers, increasing the effective reproduction number above 1 and thus increasing the risk of localized outbreaks. If relaxation is, instead, delayed and 75% of the Ontarian population gets vaccinated by the end of the year, re-opening can occur with very little risk. Relaxing non-pharmaceutical interventions by re-opening and vaccine deployment is a careful balancing act. Our combination of model projections from data and simulation of different strategies and scenarios, can equip local public health decision- and policy-makers with projections concerning the COVID-19 epidemiological trend, helping them in the decision-making process.

A Multicriteria Spatiotemporal System for Influenza Epidemic Surveillance

2019 ◽  
pp. 176-202
Author(s):  
Fatima-Zohra Younsi ◽  
Djamila Hamdadou ◽  
Salem Chakhar
Keyword(s):  
Public Health ◽  
High Risk ◽  
Seasonal Influenza ◽  
Control Strategies ◽  
Ranking Method ◽  
Influenza Surveillance ◽  
Policy Makers ◽  
Promethee Ii ◽  
Public Health Decision ◽  
Health Decision

Influenza has been a growing concern for the public health decision makers/policy makers. Indeed, they are in need of a real geo-making tool for monitoring and surveillance. The chapter aims to introduce a novel spatiotemporal decision system based on multicriteria ranking method, information geographic system (GIS), and SEIRSW system for public health. The later was designed, implemented, and validated in previous research for influenza risk assessment. The authors highlight the use of PROMETHEE II ranking method of multi-criteria decision analysis in GIS that incorporates various factors to monitor and identify potential high-risk areas of seasonal influenza and disease mapping. Factors related to the risk of seasonal influenza are obtained from simulation system and constitute the input values of PROMETHEE II ranking method for the 26 communes of the city of Oran, Algeria. The proposed system has demonstrated analytical capabilities in targeting high-risk spots and influenza surveillance monitoring system and it can help public health policy makers prioritize in their response goals and evaluate control strategies.

scholarly journals Does High Population Density Catalyze the Spread of COVID-19?

2020 ◽  
Vol 23 (s1) ◽  
pp. 13-27
Author(s):  
Berislav Žmuk ◽  
Hrvoje Jošić
Keyword(s):  
Public Health ◽  
Population Density ◽  
Economic Problem ◽  
Economic Sectors ◽  
Policy Makers ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Country Level ◽  
Health Decision ◽  
Variable Population

Abstract COVID-19 represents not only public health emergency but has become a global economic problem. It has affected all economic sectors threatening global poverty. The important question that arises is what catalyses the spread of the disease? In this paper the relationship between population density and spread of COVID-19 is observed which is goal of the paper. For the purpose of the analysis the correlation between the population variables and COVID-19 variables on a global country level (209 countries) and regional level of individual countries with the most cases of infection is observed. The results have shown that on a country level variable population is statistically significant in all regression models for total cases, deaths and total tests variables whereas variable population density was not. The research results from this paper can be important and relevant for economic and health policy makers to guide COVID-19 surveillance and public health decision-making.

scholarly journals Integrated Vaccination and Non-Pharmaceutical Interventions based Strategies in Ontario, Canada, as a Case Study: a Mathematical Modeling Study

2021 ◽  
Author(s):  
Matthew Betti ◽  
Nicola Bragazzi ◽  
Jane Heffernan ◽  
Jude Dvezela Kong ◽  
Angie Raad
Keyword(s):  
Public Health ◽  
Control Measures ◽  
Policy Makers ◽  
Local Public Health ◽  
Public Health Decision ◽  
The Public ◽  
Epidemiological Trend ◽  
Health Decision ◽  
Pharmaceutical Interventions

Background: Recently, two "Coronavirus disease 2019" (COVID-19) vaccine products have been authorized in Canada. It is of crucial importance to model an integrated/combined package of non-pharmaceutical (physical/social distancing) and pharmaceutical (immunization) public health control measures. Methods: A modified epidemiological, compartmental SIR model was utilized and fit to the cumulative COVID-19 case data for the province of Ontario, Canada, from September 8, 2020 to December 8, 2020. Different vaccine roll-out strategies were simulated until 75 percent of the population is vaccinated, including a no-vaccination scenario. We compete these vaccination strategies with relaxation of non-pharmaceutical interventions. Non-pharmaceutical interventions were supposed to remain enforced and began to be relaxed on either January 31, March 31, or May 1, 2021. Results: Based on projections from the data and long-term extrapolation of scenarios, relaxing the public health measures implemented by re-opening too early would cause any benefits of vaccination to be lost by increasing case numbers, increasing the effective reproduction number above 1 and thus increasing the risk of localized outbreaks. If relaxation is, instead, delayed and 75 percent of the Ontarian population gets vaccinated by the end of the year, re-opening can occur with very little risk. Interpretation: Relaxing non-pharmaceutical interventions by re-opening and vaccine deployment is a careful balancing act. Our combination of model projections from data and simulation of different strategies and scenarios, can equip local public health decision- and policy-makers with projections concerning the COVID-19 epidemiological trend, helping them in the decision-making process.

Persons with Disabilities and Public Health Ethics

2019 ◽  
pp. 218-231
Author(s):  
Monika Mitra ◽  
Linda Long-Bellil ◽  
Robyn Powell
Keyword(s):  
Public Health ◽  
Health Policy ◽  
Public Health Policy ◽  
Ethical Issues ◽  
The United States ◽  
Policy And Practice ◽  
Persons With Disabilities ◽  
Public Health Decision ◽  
Health Decision ◽  
Health Policy And Practice

This chapter draws on medical, social, and legal perspectives to identify and highlight ethical issues pertaining to the treatment, representation, and inclusion of persons with disabilities in public health policy and practice. A brief history of disability in the United States is provided as a context for examining the key ethical issues related to public health policy and practice. Conceptual frameworks and approaches to disability are then described and applied. The chapter then discusses the imperativeness of expanding access to public health programs by persons with disabilities, the need to address implicit and structural biases, and the importance of including persons with disabilities in public health decision-making.

scholarly journals The NCCMT’s dynamic model for evidence-informed public health

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
E Clark ◽  
S Neil-Sztramko ◽  
M Dobbins
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Research Evidence ◽  
Decision Makers ◽  
Local Data ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Political Preferences ◽  
Health Decision ◽  
Structured Approach

Abstract Issue It is well accepted that public health decision makers should use the best available research evidence in their decision-making process. However, research evidence alone is insufficient to inform public health decision making. Description of the problem As new challenges to public health emerge, there can be a paucity of high quality research evidence to inform decisions on new topics. Public health decision makers must combine various sources of evidence with their public health expertise to make evidence-informed decisions. The National Collaborating Centre for Methods and Tools (NCCMT) has developed a model which combines research evidence with other critical sources of evidence that can help guide decision makers in evidence-informed decision making. Results The NCCMT's model for evidence-informed public health combines findings from research evidence with local data and context, community and political preferences and actions and evidence on available resources. The model has been widely used across Canada and worldwide, and has been integrated into many public health organizations' decision-making processes. The model is also used for teaching an evidence-informed public health approach in Masters of Public Health programs around the globe. The model provides a structured approach to integrating evidence from several critical sources into public health decision making. Use of the model helps ensure that important research, contextual and preference information is sought and incorporated. Lessons Next steps for the model include development of a tool to facilitate synthesis of evidence across all four domains. Although Indigenous knowledges are relevant for public health decision making and should be considered as part of a complete assessment the current model does not capture Indigenous knowledges. Key messages Decision making in public health requires integrating the best available evidence, including research findings, local data and context, community and political preferences and available resources. The NCCMT’s model for evidence-informed public health provides a structured approach to integrating evidence from several critical sources into public health decision making.

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