scholarly journals Optimizing the spatio-temporal allocation of COVID-19 vaccines: Italy as a case study

2021 ◽  
Author(s):  
Joseph Chadi Lemaitre ◽  
Damiano Pasetto ◽  
Mario Zanon ◽  
Enrico Bertuzzo ◽  
Lorenzo Mari ◽  
...  
Keyword(s):  
Optimal Control ◽  
Disease Transmission ◽  
Population Distribution ◽  
Transmission Rate ◽  
Supply And Distribution ◽  
Simple Alternative ◽  
Spatio Temporal ◽  
Vaccine Distribution ◽  
Vaccination Campaigns ◽  
Allocation Strategies

While SARS-CoV-2 vaccine distribution campaigns are underway across the world, communities face the challenge of a fair and effective distribution of limited supplies. We wonder whether suitable spatial allocation strategies might significantly improve a campaign's efficacy in averting damaging outcomes. To that end, we address the problem of optimal control of COVID-19 vaccinations in a country-wide geographic and epidemiological context characterized by strong spatial heterogeneities in transmission rate and disease history. We seek the vaccine allocation strategies in space and time that minimize the number of infections in a prescribed time horizon. We examine scenarios of unfolding disease transmission across the 107 provinces of Italy, from January to April 2021, generated by a spatially explicit compartmental COVID-19 model tailored to the Italian geographic and epidemiological context. We develop a novel optimal control framework to derive optimal vaccination strategies given the epidemiological projections and constraints on vaccine supply and distribution logistic. Optimal schemes significantly outperform simple alternative allocation strategies based on incidence, population distribution, or prevalence of susceptibles in each province. Our results suggest that the complex interplay between the mobility network and the spatial heterogeneities imply highly non-trivial prioritization of local vaccination campaigns. The extent of the overall improvements in the objectives grants further inquiry aimed at refining other possibly relevant factors so far neglected. Our work thus provides a proof-of-concept of the potential of optimal control for complex and heterogeneous epidemiological contexts at country, and possibly global, scales.

scholarly journals Optimal Allocation of Vaccine and Antiviral Drugs for Influenza Containment over Delayed Multiscale Epidemic Model considering Time-Dependent Transmission Rate

2021 ◽  
Vol 2021 ◽  
pp. 1-27
Author(s):  
Zohreh Abbasi ◽  
Iman Zamani ◽  
Amir Hossein Amiri Mehra ◽  
Asier Ibeas ◽  
Mohsen Shafieirad
Keyword(s):  
Optimal Control ◽  
Time Delay ◽  
Epidemic Model ◽  
Disease Transmission ◽  
Optimal Allocation ◽  
Transmission Rate ◽  
Antiviral Treatment ◽  
Infected Individual ◽  
Optimal Time ◽  
Control Input

In this study, two types of epidemiological models called “within host” and “between hosts” have been studied. The within-host model represents the innate immune response, and the between-hosts model signifies the SEIR (susceptible, exposed, infected, and recovered) epidemic model. The major contribution of this paper is to break the chain of infectious disease transmission by reducing the number of susceptible and infected people via transferring them to the recovered people group with vaccination and antiviral treatment, respectively. Both transfers are considered with time delay. In the first step, optimal control theory is applied to calculate the optimal final time to control the disease within a host’s body with a cost function. To this end, the vaccination that represents the effort that converts healthy cells into resistant-to-infection cells in the susceptible individual’s body is used as the first control input to vaccinate the susceptible individual against the disease. Moreover, the next control input (antiviral treatment) is applied to eradicate the concentrations of the virus and convert healthy cells into resistant-to-infection cells simultaneously in the infected person’s body to treat the infected individual. The calculated optimal time in the first step is considered as the delay of vaccination and antiviral treatment in the SEIR dynamic model. Using Pontryagin’s maximum principle in the second step, an optimal control strategy is also applied to an SEIR mathematical model with a nonlinear transmission rate and time delay, which is computed as optimal time in the first step. Numerical results are consistent with the analytical ones and corroborate our theoretical results.

scholarly journals The importance of non-pharmaceutical interventions during the COVID-19 vaccine rollout

2021 ◽  
Vol 17 (9) ◽  
pp. e1009346
Author(s):  
Nicolò Gozzi ◽  
Paolo Bajardi ◽  
Nicola Perra
Keyword(s):  
Disease Transmission ◽  
Compartmental Model ◽  
Short Term ◽  
Mobility Data ◽  
History Of ◽  
Age Structured ◽  
Vaccine Distribution ◽  
Vaccination Campaigns ◽  
Behavioural Dynamics ◽  
Pharmaceutical Interventions

The promise of efficacious vaccines against SARS-CoV-2 is fulfilled and vaccination campaigns have started worldwide. However, the fight against the pandemic is far from over. Here, we propose an age-structured compartmental model to study the interplay of disease transmission, vaccines rollout, and behavioural dynamics. We investigate, via in-silico simulations, individual and societal behavioural changes, possibly induced by the start of the vaccination campaigns, and manifested as a relaxation in the adoption of non-pharmaceutical interventions. We explore different vaccination rollout speeds, prioritization strategies, vaccine efficacy, as well as multiple behavioural responses. We apply our model to six countries worldwide (Egypt, Peru, Serbia, Ukraine, Canada, and Italy), selected to sample diverse socio-demographic and socio-economic contexts. To isolate the effects of age-structures and contacts patterns from the particular pandemic history of each location, we first study the model considering the same hypothetical initial epidemic scenario in all countries. We then calibrate the model using real epidemiological and mobility data for the different countries. Our findings suggest that early relaxation of safe behaviours can jeopardize the benefits brought by the vaccine in the short term: a fast vaccine distribution and policies aimed at keeping high compliance of individual safe behaviours are key to mitigate disease resurgence.

scholarly journals Dynamics of Drug Resistance: Optimal Control of an Infectious Disease

2019 ◽  
Vol 67 (3) ◽  
pp. 619-650 ◽  
Author(s):  
Naveed Chehrazi ◽  
Lauren E. Cipriano ◽  
Eva A. Enns
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Optimal Control ◽  
Drug Resistance ◽  
Disease Transmission ◽  
Transmission Rate ◽  
Treatment Options ◽  
Treatment Resistance ◽  
State Variables ◽  
Public Health Challenge

Antimicrobial use contributes to the growing public health challenge of infectious diseases that are resistant to all but a few remaining treatments via natural selection. When few treatment options remain, should the last effective treatment be reserved for controlling larger outbreaks in the future? In “Dynamics of Drug Resistance: Optimal Control of an Infectious Disease,” N. Chehrazi, L. E. Cipriano, and E. A. Enns formulate this important policy question as a control problem with two state variables—disease prevalence and the level of treatment resistance—for an established family of SIS infectious disease models with resistance. They prove that when the disease transmission rate is constant, it is optimal to treat everyone until the level of resistance is so high that it is no longer economical to treat anyone. Public health policies and social distancing can cause a nonconstant disease transmission rate; in these cases, it may be optimal to preserve the drug for relatively larger outbreaks or to use the drug to treat some, but not all, infected individuals.

scholarly journals Estimating asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan: a mathematical modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Transmission Rate ◽  
Control Strategies ◽  
Herd Immunity ◽  
Antibody Prevalence ◽  
Screening Process ◽  
Vaccination Programs ◽  
Prevalence Level ◽  
The Impact

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

scholarly journals The effects of flooding and weather conditions on leptospirosis transmission in Thailand

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sudarat Chadsuthi ◽  
Karine Chalvet-Monfray ◽  
Anuwat Wiratsudakul ◽  
Charin Modchang
Keyword(s):  
Sensitivity Analysis ◽  
Public Education ◽  
Mathematical Models ◽  
Disease Transmission ◽  
Transmission Rate ◽  
Weather Conditions ◽  
Transmission Dynamics ◽  
Multiplication Rate ◽  
High Degree ◽  
Transmission Models

AbstractThe epidemic of leptospirosis in humans occurs annually in Thailand. In this study, we have developed mathematical models to investigate transmission dynamics between humans, animals, and a contaminated environment. We compared different leptospire transmission models involving flooding and weather conditions, shedding and multiplication rate in a contaminated environment. We found that the model in which the transmission rate depends on both flooding and temperature, best-fits the reported human data on leptospirosis in Thailand. Our results indicate that flooding strongly contributes to disease transmission, where a high degree of flooding leads to a higher number of infected individuals. Sensitivity analysis showed that the transmission rate of leptospires from a contaminated environment was the most important parameter for the total number of human cases. Our results suggest that public education should target people who work in contaminated environments to prevent Leptospira infections.

scholarly journals Mother-child transmission of Chagas disease: could coinfection with human immunodeficiency virus increase the risk?

2009 ◽  
Vol 42 (2) ◽  
pp. 107-109 ◽  
Author(s):  
Pablo Gustavo Scapellato ◽  
Edgardo Gabriel Bottaro ◽  
María Teresa Rodríguez-Brieschke
Keyword(s):  
Human Immunodeficiency Virus ◽  
Trypanosoma Cruzi ◽  
Chagas Disease ◽  
Vertical Transmission ◽  
Disease Transmission ◽  
Transmission Rate ◽  
Buffy Coat ◽  
Child Transmission ◽  
Serological Tests ◽  
Immunodeficiency Virus

A study was conducted on all newborns from mothers with Chagas disease who were attended at Hospital Donación F. Santojanni between January 1, 2001, and August 31, 2007. Each child was investigated for the presence of Trypanosoma cruzi parasitemia through direct examination of blood under the microscope using the buffy coat method on three occasions during the first six months of life. Serological tests were then performed. Ninety-four children born to mothers infected with Trypanosoma cruzi were attended over the study period. Three of these children were born to mothers coinfected with the human immunodeficiency virus. Vertical transmission of Chagas disease was diagnosed in 13 children, in all cases by identifying parasitemia. The overall Chagas disease transmission rate was 13.8% (13/94). It was 100% (3/3) among the children born to mothers with HIV infection and 10.9% (10/91) among children born to mothers without HIV [Difference = 0.89; CI95 = 0.82-0.95; p = 0.0021]. We concluded that coinfection with HIV could increase the risk of vertical transmission of Chagas disease.

scholarly journals Modeling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil

2021 ◽  
Author(s):  
Marcelo Eduardo Borges ◽  
Leonardo Souto Ferreira ◽  
Silas Poloni ◽  
Ângela Maria Bagattini ◽  
Caroline Franco ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Transmission Rate ◽  
Disease Incidence ◽  
Demographic Data ◽  
School Closure ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
School Closures ◽  
Infection Transmission ◽  
The Impact

Among the various non–pharmaceutical interventions implemented in response to the Covid–19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long–term impacts of prolonged suspension of in–person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of Covid–19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening. Our model shows that reopening schools results in a non–linear increase of reported Covid-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within[&ndash]school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.

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