Increasing molecular diagnostic capacity and COVID-19 incidence in Brazil

SARS-CoV-2 self-testing in Peru: a cross-sectional survey of values and attitudes of the general population

OBJECTIVES

To assess the values of and attitudes towards the use of rapid SARS-CoV-2 antigen-detection tests for self-testing in a rural and an urban area in Peru.

DESIGN

Cross-sectional, street-based population survey.

SETTING

A series of over 400 randomly selected street points in Valle del Mantaro and in Lima.

PARTICIPANTS

438 respondents (203 female) participated. They were all older than 17 years and provided informed consent for participation.

INTERVENTION

All respondents answered on the spot, a 35-item questionnaire developed in KoboToolbox.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes of interest were: likelihood to use a SARS-CoV-2 self-test; willingness to pay for a SARS-CoV-2 self-test and likelihood to comply with recommended actions following a positive SARS-CoV-2 self-test result. Bivariate analyses and Poisson regression (PR) analyses were performed to identify significant associations between dependent variables and independent variables pertaining to respondents' characteristics, risk perception and previous experiences with conventional COVID-19 testing.

RESULTS

Of the 438 respondents, 51.49% had previous experience with conventional COVID-19 testing; 20.37% had COVID-19 disease; 86.96% accepted the idea of SARS-CoV-2 self-testing; and, 78.95% would be likely to use it if needed. Almost all (94.75%) would pay for a self-testing device (mean acceptable payment: US$10.4) if it was not provided free of charge by health authorities. Overall, 93.12%, 86.93% and 85.32% would self-isolate, report the results and warn their contacts, respectively. Being a female (adjusted PR 1.05, 95% CI 1.00 to 1.09, p<0.018), having completed secondary education (adjusted PR 1.18, 95% CI 1.02 to 1.37, p<0.024) and expressing likelihood to use self-testing (adjusted PR 1.08, 95% CI 1.01 to 1.16, p<0.0.24) could be predictors of willingness to pay for a self-test.

CONCLUSIONS

Self-testing is perceived as an acceptable approach. Health authorities in Peru should facilitate access to this approach to complement healthcare facilities-led testing efforts for COVID-19. Future research is necessary to understand the impact of self-testing in case detection and pandemic control.

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil

The COVID-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighborhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12–0.80%), followed by 2.69% (90% CI 1.88–3.49%) in the second survey and 6.67% (90% CI 5.42–7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25–2.82), while the single best predictor for positivity was ageusia/anosmia (OR 8.12, 95% CI 4.72–13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to adequately describe COVID-19 dispersion in the city. Presented results have helped local government authorities to guide pandemic management.

Implementation of large-scale laboratory-based detection of COVID-19 in the Veterans Health Administration, March 2020 - February 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presented numerous operational challenges to healthcare delivery networks responsible for implementing large scale detection of Coronavirus Disease 2019 (COVID-19), the infection caused by SARS-CoV-2. We describe testing performance, review data quality metrics, and summarize experiences during the scale up of laboratory-based detection of COVID-19 in the Veterans Health Administration, the largest healthcare system in the United States. During March 2020 to February 2021, we observed rapid increase in testing volume, decreases in test turnaround time, improvements in testing of hospitalized persons, changes in test positivity, and varying utilization of different tests. Though performance metrics improved over time, surges challenged testing capacity and data quality remained suboptimal. Future planning efforts should focus on fortifying supply chains for consumables and equipment repair, optimizing distribution of testing workload across laboratories, and improving informatics to accurately monitor operations and intent for testing during a public health emergency.

A snapshot of a pandemic: The interplay between social isolation and COVID-19 dynamics in Brazil

In response to the coronavirus pandemic, governments implemented social distancing, attempting to block the virus spread within territories. While it is well accepted that social isolation plays a role in epidemic control, the precise connections between mobility data indicators and epidemic dynamics are still a challenge. In this work, we investigate the dependency between a social isolation index and epidemiological metrics for several Brazilian cities. Classic statistical methods are employed to support the findings. As a first, initially surprising, result, we illustrate how there seems to be no apparent functional relationship between social isolation data and later effects on disease incidence. However, further investigations identified two regimes of successful employment of social isolation: as a preventive measure or as a remedy, albeit remedy measures require greater social isolation and bring higher burden to health systems. Additionally, we exhibit cases of successful strategies involving lockdowns and an indicator-based mobility restriction plan.

Addressing the COVID-19 transmission in inner Brazil by a mathematical model

In 2020, the world experienced its very first pandemic of the globalized era. A novel coronavirus, SARS-CoV-2, is the causative agent of severe pneumonia and has rapidly spread through many nations, crashing health systems and leading a large number of people to death. In Brazil, the emergence of local epidemics in major metropolitan areas has always been a concern. In a vast and heterogeneous country, with regional disparities and climate diversity, several factors can modulate the dynamics of COVID-19. What should be the scenario for inner Brazil, and what can we do to control infection transmission in each of these locations? Here, a mathematical model is proposed to simulate disease transmission among individuals in several scenarios, differing by abiotic factors, social-economic factors, and effectiveness of mitigation strategies. The disease control relies on keeping all individuals’ social distancing and detecting, followed by isolating, infected ones. The model reinforces social distancing as the most efficient method to control disease transmission. Moreover, it also shows that improving the detection and isolation of infected individuals can loosen this mitigation strategy. Finally, the effectiveness of control may be different across the country, and understanding it can help set up public health strategies.

The use of health geography modeling to understand early dispersion of COVID-19 in São Paulo, Brazil

Public health policies to contain the spread of COVID-19 rely mainly on non-pharmacological measures. Those measures, especially social distancing, are a challenge for developing countries, such as Brazil. In São Paulo, the most populous state in Brazil (45 million inhabitants), most COVID-19 cases up to April 18th were reported in the Capital and metropolitan area. However, the inner municipalities, where 20 million people live, are also at risk. As governmental authorities discuss the loosening of measures for restricting population mobility, it is urgent to analyze the routes of dispersion of COVID-19 in São Paulo territory. We hypothesize that urban hierarchy is the main responsible for the disease spreading, and we identify the hotspots and the main routes of virus movement from the metropolis to the inner state. In this ecological study, we use geographic models of population mobility to check for patterns for the spread of SARS-CoV-2 infection. We identify two patterns based on surveillance data: one by contiguous diffusion from the capital metropolitan area, and the other hierarchical with long-distance spread through major highways that connects São Paulo city with cities of regional relevance. This knowledge can provide real-time responses to support public health strategies, optimizing the use of resources in order to minimize disease impact on population and economy.

Two hundred days of COVID-19 in São Paulo State, Brazil

Two hundred days after the first confirmed case of COVID-19 in Brazil, the epidemic has rapidly spread in metropolitan areas and advanced throughout the countryside. We followed the temporal epidemic pattern at São Paulo State, the most populous of the country, the first to have a confirmed case of COVID-19, and the one with the most significant number of cases until now. We analysed the number of new cases per day in each regional health department and calculated the effective reproduction number (R_t) over time. Social distance measures, along with improvement in testing and isolating positive cases, general population mask-wearing and standard health security protocols for essential and non-essential activities, were adopted and impacted on slowing down epidemic velocity but were insufficient to stop transmission.