Modelling the test, trace and quarantine strategy to control the COVID-19 epidemic in the state of São Paulo, Brazil.

Testing for detecting the infection by SARS-CoV-2 is the bridge between the lockdown and the opening of society. In this paper we modelled and simulated a test-trace-and-quarantine strategy to control the COVID-19 outbreak in the State of São Paulo, Brasil. The State of São Paulo failed to adopt an effective social distancing strategy, reaching at most 59% in late March and started to relax the measures in late June, dropping to 41% in 08 August. Therefore, São Paulo relies heavily on a massive testing strategy in the attempt to control the epidemic. Two alternative strategies combined with economic evaluations were simulated. One strategy included indiscriminately testing the entire population of the State, reaching more than 40 million people at a maximum cost of 2.25 billion USD, that would reduce the total number of cases by the end of 2020 by 90%. The second strategy investigated testing only symptomatic cases and their immediate contacts - this strategy reached a maximum cost of 150 million USD but also reduced the number of cases by 90%. The conclusion is that if the State of São Paulo had decided to adopt the simulated strategy on April the 1st, it would have been possible to reduce the total number of cases by 90% at a cost of 2.25 billion US dollars for the indiscriminate strategy but at a much smaller cost of 125 million US dollars for the selective testing of symptomatic cases and their contacts.

The risk of malaria infection for travelers visiting the Brazilian Amazonian region: A mathematical modeling approach.

BACKGROUND: Human mobility between malaria endemic and malaria-free areas can hinder control and elimination efforts in the Amazon basin, maintaining Plasmodium circulation and introduction to new areas. METHODS: The analysis begins by estimating the incidence of malaria in areas of interest. Then, the risk of infection as a function of the duration of stay after t0 was calculated as the number of infected travelers over the number of arrived travelers. Differential equations were employed to estimate the risk of nonimmune travelers acquiring malaria in Amazonian municipalities. Risk was calculated as a result of the force of the infection in terms of local dynamics per time of arrival and duration of visit. RESULTS: Maximum risk occurred at the peak or at the end of the rainy season and it was nonlinearly (exponentially) correlated with the fraction of infected mosquitoes. Relationship between the risk of malaria and duration of visit was linear and positively correlated. Relationship between the risk of malaria and the time of arrival in the municipality was dependent on local effects of seasonality. CONCLUSIONS: The risk of nonimmune travelers acquiring malaria is not negligible and can maintain regional circulation of parasites, propagating introductions in areas where malaria has been eliminated.

A Model-Based Strategy to Control the Spread of Carbapenem-Resistant Enterobacteriaceae: Simulate and Implement.

OBJECTIVE To reduce transmission of carbapenem-resistant Enterobacteriaceae (CRE) in an intensive care unit with interventions based on simulations by a developed mathematical model. DESIGN Before-after trial with a 44-week baseline period and 24-week intervention period. SETTING Medical intensive care unit of a tertiary care teaching hospital. PARTICIPANTS All patients admitted to the unit. METHODS We developed a model of transmission of CRE in an intensive care unit and measured all necessary parameters for the model input. Goals of compliance with hand hygiene and with isolation precautions were established on the basis of the simulations and an intervention was focused on reaching those metrics as goals. Weekly auditing and giving feedback were conducted. RESULTS The goals for compliance with hand hygiene and contact precautions were reached on the third week of the intervention period. During the baseline period, the calculated R0 was 11; the median prevalence of patients colonized by CRE in the unit was 33%, and 3 times it exceeded 50%. In the intervention period, the median prevalence of colonized CRE patients went to 21%, with a median weekly Rn of 0.42 (range, 0-2.1). CONCLUSIONS The simulations helped establish and achieve specific goals to control the high prevalence rates of CRE and reduce CRE transmission within the unit. The model was able to predict the observed outcomes. To our knowledge, this is the first study in infection control to measure most variables of a model in real life and to apply the model as a decision support tool for intervention. Infect Control Hosp Epidemiol 2016;1-8.