Quantifying protocols for safe school activities (preprint)

By the peak of COVID-19 restrictions on April 8, 2020, up to 1.5 billion students across 188 countries were by the suspension of physical attendance in schools. Schools were among the first services to reopen as vaccination campaigns advanced. With the emergence of new variants and infection waves, the question now is to find safe protocols for the continuation of school activities. We need to understand how reliable these protocols are under different levels of vaccination coverage, as many countries have a meager fraction of their population vaccinated, including Uganda where the coverage is about 8\%. We investigate the impact of face-to-face classes under different protocols and quantify the surplus number of infected individuals in a city. Using the infection transmission when schools were closed as a baseline, we assess the impact of physical school attendance in classrooms with poor air circulation. We find that (i) resuming school activities with people only wearing low-quality masks leads to a near fivefold city-wide increase in the number of cases even if all staff is vaccinated, (ii) resuming activities with students wearing good-quality masks and staff wearing N95s leads to about a threefold increase, (iii) combining high-quality masks and active monitoring, activities may be carried out safely even with low vaccination coverage. These results highlight the effectiveness of good mask-wearing. Compared to ICU costs, high-quality masks are inexpensive and can help curb the spreading. Classes can be carried out safely, provided the correct set of measures are implemented.

Impact of Liver Test Abnormalities and Chronic Liver Disease on the Clinical Outcomes of Patients Hospitalized with COVID-19

Background and Aims: The impact of SARS-CoV-2 infection on the liver and the possibility of chronic liver disease (CLD) as a risk factor for COVID-19 severity is not fully understood. Our goal was to describe clinical outcomes of COVID-19 inpatients regarding the presence of abnormal liver tests and CLD. Methods: A retrospective analysis of patients with SARS-CoV-2 infection, hospitalized in a tertiary center in Portugal, was performed. Studied outcomes were disease and hospitalization length, COVID-19 severity, admission to intensive care unit (ICU) and mortality, analyzed by the presence of abnormal liver tests and CLD. Results: We included 317 inpatients with a mean age of 70.4 years, 50.5% males. COVID-19 severity was moderate to severe in 57.4% and critical in 12.9%. The mean disease length was 37.8 days, the median hospitalization duration 10.0 days and overall mortality 22.8%. At admission, 50.3% showed abnormal liver tests, and 41.5% showed elevated aminotransferase levels, from which 75.4% were mild. Elevated aminotransferase levels at admission were associated with COVID-19 severity (78.7 vs. 63.3%, p = 0.01), ICU admission (13.1 vs. 5.92%, p = 0.034) and increased mortality (25.8 vs. 13.3%, p = 0.007). However, in a subgroup analysis, only aspartate transaminase (AST) was associated with these worse outcomes. Alkaline phosphatase was elevated in 11.4% of the patients and was associated with critical COVID-19 (21.1 vs. 9.92%, p = 0.044) and mortality (20.4 vs. 9.52%, p = 0.025), while 24.6% of the patients showed elevated γ-glutamyl transferase, which was associated with ICU admission (42.3 vs. 22.8%, p = 0.028). Fourteen patients had baseline CLD (4.42%), 3 with liver cirrhosis. Alcohol (n = 6) and nonalcoholic fatty liver disease (n = 6) were the most frequent etiologies. CLD patients had critical COVID-19 in 21.4% (p = 0.237), mean disease length of 36.6 days (p = 0.291), median hospitalization duration of 11.5 days (p = 0.447) and a mortality rate of 28.6% (p = 0.595), which increased to 66.7% among cirrhotic patients (p = 0.176). Conclusions: Liver test abnormalities in COVID-19 patients were frequent but most commonly mild. AST, but not alanine transaminase, was associated with worse clinical outcomes, such as COVID-19 severity and mortality, probably indicating these outcomes were independent of liver injury. A low prevalence of CLD was seen, and a clear impact on COVID-19 outcomes was not seen.

Smart testing and critical care bed sharing for COVID-19 control (preprint)

During the early months of the current COVID-19 pandemic, social-distancing measures effectively slowed disease transmission in many countries in Europe and Asia, but the same benefits have not been observed in some developing countries such as Brazil. In part, this is due to a failure to organise systematic testing campaigns at nationwide or even regional levels. To gain effective control of the pandemic, decision-makers in developing countries, particularly those with large populations, must overcome difficulties posed by an unequal distribution of wealth combined with low daily testing capacities. The economic infrastructure of the country, often concentrated in a few cities, forces workers to travel from commuter cities and rural areas, which induces strong nonlinear effects on disease transmission. In the present study, we develop a smart testing strategy to identify geographic regions where COVID-19 testing could most effectively be deployed to limit further disease transmission. The strategy uses readily available anonymised mobility and demographic data integrated with intensive care unit (ICU) occupancy data and city-specific social-distancing measures. Taking into account the heterogeneity of ICU bed occupancy in differing regions and the stages of disease evolution, we use a data-driven study of the Brazilian state of Sao Paulo as an example to show that smart testing strategies can rapidly limit transmission while reducing the need for social-distancing measures, thus returning life to a so-called new normal, even when testing capacity is limited.

Robot dance: a city-wise automatic control of Covid-19 mitigation levels (preprint)

We develop an automatic control system to help to design efficient mitigation measures for the Covid-19 epidemic in cities. Taking into account parameters associated to the population of each city and the mobility among them, the optimal control framework suggests the level and duration of protective measures that must be implemented to ensure that the number of infected individuals is within a range that avoids the collapse of the health care system. Compared against other mitigation measures that are implemented simultaneously and in equal strength across cities our method has three major particularities when: Accounts for city commute and health infrastructure: It takes into account the daily commute among cities to estimate the dynamics of infected people while keeping the number of infected people within a desired level at each city avoiding the collapse of its health care system. City-specific control: It allows for orchestrating the control measures among cities so as to prevent all cities to face the same level control. The model tends to induce alternation between periods of stricter controls and periods of a more normal life in each city and among the cities. Flexible scenarios: It is flexible enough to allow for simulating the impact of particular actions. For example, one can simulate the how the control all cities change when the number of care beds increases in specific places. Therefore, our method creates an automatic dance adjusting mitigation levels within cities and alternating among cities as suggested in~\cite{Pue2020}. This automatic dance may help the city economy and orchestration of resources. We provide case studies using the major cities of the state of Sao Paulo given by using estimates on the daily mobility among the cities their health care system capacity. We use official data in our case studies. However, sub-notification of infected people in Brazil is notoriously high. Hence the case study should not be considered as a real world policy suggestion. It high sub-notification is taken into account, the optimal control algorithm will suggest stricter mitigation measures, as also shown in the case studies. Surprisingly, the total duration of the protocol for the state is barely affected by the sub-notification, but the severity of such protocols is strengthened. This stresses a twofold implication, first, the protocol depends on high-quality data and, second, such optimal and orchestrated protocol is robust and can be adjusted to the demand.