scholarly journals Attack rate and the price of SARS-CoV-2 herd immunity in Brazil

Author(s):  
Tarcisio Rocha Filho ◽  
José Mendes ◽  
Carson Chow ◽  
James Phillips ◽  
Antônio Cordeiro ◽  
...  

Abstract We introduce a compartmental model with age structure to study the dynamics of the SARS-COV−2 pandemic. The contagion matrix in the model is given by the product of a probability per contact with a contact matrix explicitly taking into account the contact structure among different age groups. The probability of contagion per contact is considered as time dependent to represent non-pharmaceutical interventions, and is fitted from the time series of deaths. The approach is used to study the evolution of the COVID−19 pandemic in the main Brazilian cities and compared to two good quality serological surveys. We also discuss with some detail the case of the city of Manaus which raised special attention due to a previous report of three-quarters attack rate by the end of 2020. We discuss estimates for Manaus and all Brazilian cities with a total population of more than one million. We also estimate the attack rate with respect to the total population, in each Brazilian state by January, 1 st 2021 and May, 23 2021.

2021 ◽  
Author(s):  
Tarcisio Rocha Filho ◽  
José Mendes ◽  
Carson Chow ◽  
James Phillips ◽  
Antônio Cordeiro ◽  
...  

Abstract We introduce a compartmental model with age structure to study the dynamics of the SARS-COV-2 pandemic. The contagion matrix in the model is given by the product of a probability per contact with a contact matrix explicitly taking into account the contact structure among different age groups. The probability of contagion per contact is considered as time dependent to represent non-pharmaceutical interventions, and is fitted from the time series of deaths. The approach is used to study the evolution of the COVID-19 pandemic in the main Brazilian cities and compared to two good quality serological surveys. We also discuss with some detail the case of the city of Manaus which raised special attention due to a previous report of three-quarters attack rate by the end of 2020. We discuss estimates for Manaus and all Brazilian cities with a total population of more than one million. We also estimate the attack rate with respect to the total population, in each Brazilian state by January, 1st 2021 and May, 23 2021.


Author(s):  
Sylwia Krzysztofowicz ◽  
Katarzyna Osińska-Skotak

The COVID-19 pandemic is a global challenge, and the key to tackling it is vaccinating a specified percentage of the population to acquire herd immunity. The observed problems with the efficiency of the vaccination campaigns in numerous countries around the world, as well as the approach used at the initial stage of the National Immunization Program in Poland, prompted us to analyse the possibility of using GIS technology to optimize the distribution of vaccines to vaccination sites so as to minimize the period needed to vaccinate individual population groups. The research work was carried out on the example of Warsaw, the capital of Poland and the city with the largest population in the country. The analyses were carried out for the 60–70 and 50–60 age groups, in various approaches and for vaccines of different companies (Moderna, BioNTech, AstraZeneca), used to vaccinate people in Poland. The proposed approach to optimize vaccine distribution uses Thiessen’s tessellation to obtain information on the number of people in a given population group living in the area of each vaccination site, and then to estimate the time needed to vaccinate that group. Compared to the originally used vaccination scenario with limited availability of vaccines, the proposed approach allows practitioners to design fast and efficient distribution scenarios. With the developed methodology, we demonstrated ways to achieve uniform vaccination coverage throughout the city. We anticipate that the proposed approach can be easily automated and broadly applied to various urban settings.


Author(s):  
Chaolong Wang ◽  
Li Liu ◽  
Xingjie Hao ◽  
Huan Guo ◽  
Qi Wang ◽  
...  

ABSTRACTBACKGROUNDWe described the epidemiological features of the coronavirus disease 2019 (Covid-19) outbreak, and evaluated the impact of non-pharmaceutical interventions on the epidemic in Wuhan, China.METHODSIndividual-level data on 25,961 laboratory-confirmed Covid-19 cases reported through February 18, 2020 were extracted from the municipal Notifiable Disease Report System. Based on key events and interventions, we divided the epidemic into four periods: before January 11, January 11-22, January 23 - February 1, and February 2-18. We compared epidemiological characteristics across periods and different demographic groups. We developed a susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions.RESULTSThe median age of the cases was 57 years and 50.3% were women. The attack rate peaked in the third period and substantially declined afterwards across geographic regions, sex and age groups, except for children (age <20) whose attack rate continued to increase. Healthcare workers and elderly people had higher attack rates and severity risk increased with age. The effective reproductive number dropped from 3.86 (95% credible interval 3.74 to 3.97) before interventions to 0.32 (0.28 to 0.37) post interventions. The interventions were estimated to prevent 94.5% (93.7 to 95.2%) infections till February 18. We found that at least 59% of infected cases were unascertained in Wuhan, potentially including asymptomatic and mild-symptomatic cases.CONCLUSIONSConsiderable countermeasures have effectively controlled the Covid-19 outbreak in Wuhan. Special efforts are needed to protect vulnerable populations, including healthcare workers, elderly and children. Estimation of unascertained cases has important implications on continuing surveillance and interventions.


2020 ◽  
Author(s):  
Vahid S. Bokharaie

AbstractThis paper presents a method to predict the spread of the SARS-CoV-2 in a population with a known age-structure, and then, to quantify the effects of various containment policies, including those policies that affect each age-group differently. The model itself is a compartmental model in which each compartment is divided into a number of age-groups. The parameter of the model are estimated using an optimisation scheme and some known results from the theory of monotone systems such that the model output agrees with some collected data on the spread of SARS-CoV-2.To highlight the strengths of this framework, a few case studies are presented in which different populations are subjected to different containment strategies. They include cases in which the containment policies switch between scenarios with different levels of severity. Then a case study on herd immunity due to vaccination is presented. And then it is shown how we can use this framework to optimality distribute a limited number of vaccine units in a given population to maximise their impact and lower the total number of infectious individuals.MSC subclass92C60, 92C50


2021 ◽  
Author(s):  
Daihai He ◽  
Yael Artzy-Randrup ◽  
Salihu S. Musa ◽  
Lewi Stone

AbstractThe arrival of SARS-COV-2 in late March 2020 in the state of Amazonas, Brazil, captured worldwide attention and concern. The rapid growth of the epidemic, a health system that had collapsed, and mass gravesites for coping with growing numbers of dead, were broadcast by the media around the world. Moreover, a majority of the local Amazonian indigenous communities were physically distant from appropriate medical services, to the point where warnings of genocide were issued. In a recent Science paper (December 2020), Buss et al. reported that some 76% of the residents of the city of Manaus, the capital of Amazonas, had been infected by October 2020. This estimate of the COVID-19 attack rate was based on a seroprevalence analysis of blood donor data, which despite its shortcomings was thought to be a sufficiently reliable proxy of the larger population. An attack rate of this magnitude (76%) implied that herd immunity had already been reached and the community was relatively protected from further infection. Yet in December 2020, a harsh second wave of COVID-19 struck Manaus, and currently appears to be even larger than the first wave. Here we use mathematical modelling of mortality data in Manaus, and in various states of Brazil, to understand why a second wave appeared against all expectations. Our analysis is based on estimating a “flexible” reproductive number R0(t) from the mortality data, as it changes in time over the epidemic.


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247439
Author(s):  
Vahid S. Bokharaie

This paper presents a method to predict the spread of the SARS-CoV-2 in a population with a known age-structure, and then, to quantify the effects of various containment policies, including those policies that affect each age-group differently. The model itself is a compartmental model in which each compartment is divided into a number of age-groups. The parameters of the model are estimated using an optimisation scheme and some known results from the theory of monotone systems such that the model output agrees with some collected data on the spread of SARS-CoV-2. To highlight the strengths of this framework, a few case studies are presented in which different populations are subjected to different containment strategies. They include cases in which the containment policies switch between scenarios with different levels of severity. Then a case study on herd immunity due to vaccination is presented. And then it is shown how we can use this framework to optimally distribute a limited number of vaccine units in a given population to maximise their impact and reduce the total number of infectious individuals.


2020 ◽  
Author(s):  
S. Celaschi

AbstractA simple and well known epidemiological deterministic model was selected to estimate the main results for the basic dynamics of the Covid-19 epidemic breakout in the city of São Paulo – Brazil. The methodology employed the SEIR Model to characterize the epidemics outbreak and future outcomes. A time-dependent incidence weight on the SEIR reproductive basic number accounts for local Mitigation Policies (MP). The insights gained from analysis of these successful interventions were used to quantify shifts and reductions on active cases, casualties, and estimatives on required medical facilities (ITU). This knowledge can be applied to other Brazilian areas. The analysis was applied to forecast the consequences of releasing the MP over specific periods of time. Herd Immunity (HI) analysis allowed estimating how far we are from reaching the HI threshold value, and the price to be paid.


2021 ◽  
Author(s):  
Naiara C.M. Valiati ◽  
Daniel A.M. Villela

SummaryThe perspective of vaccination to protect human population from infection of SARS-CoV-2 virus has great potential to control the pandemic. Nevertheless, vaccine planning requires phased introduction with age groups, health workers, and vulnerable people. We developed a mathematical model capable of capturing the dynamics of the SARS-CoV-2 dissemination aligned with social distancing, isolation measures, and vaccination. The city of Rio de Janeiro provides a case study to analyze possible scenarios including non–pharmaceutical interventions and vaccination in the epidemic scenario. Our results shows that a combination of different policies such as case isolation and social distancing are more effective for mitigating the epidemics. Furthermore, these policies will still be necessary in a phased vaccination program. Therefore, health surveillance activities should be maintained along with vaccination planning in scheduled groups until a large vaccinated coverage is reached.


2020 ◽  
Author(s):  
Guilherme Thomaz ◽  
Denis Mauá ◽  
Leliane Barros

We use data from the 2017 Origin-Destination survey to build a representative contact network for the city of São Paulo, where individuals are connected by different social relations (school, work, neighborhood, household). The network is used to devise a discrete time and state compartmental model for the spread of the COVID-19. We employed the model to compare different mitigation strategies. The results show that even simple Monte Carlo planners greatly improve the performance over reactive strategies in terms of balancing the economical and the health impacts of non-pharmaceutical interventions.


Author(s):  
Michaela A. C. Vollmer ◽  
Swapnil Mishra ◽  
H Juliette T Unwin ◽  
Axel Gandy ◽  
Thomas A Mellan ◽  
...  

Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28,238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. New interventions, such as enhanced testing and contact tracing are going to be introduced and will likely contribute to reductions in transmission; therefore our estimates should be viewed as pessimistic projections. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a second wave will not be immediately apparent from just monitoring of the daily number of deaths. Our results suggest that SARS-CoV-2 transmission as well as mobility should be closely monitored in the next weeks and months. To compensate for the increase in mobility that will occur due to the relaxation of the currently implemented NPIs, adherence to the recommended social distancing measures alongside enhanced community surveillance including swab testing, contact tracing and the early isolation of infections are of paramount importance to reduce the risk of resurgence in transmission.


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