Simulated estimates of number of silicosis cases and annual tuberculosis (TB) cases at cumulative RCS distributions of increasing mean values. by Patrick Howlett (2612374)

Parameters values for the baseline scenario correspond to the posterior median value <i>β</i>_<i>base</i> = 0.31, <i>ω</i>_<i>base</i> = 0.12, λ<sub><i>v</i>1</... by Maria L. Daza–Torres (12568896)

Excel spreadsheet including, in separate sheets, all numerical values used for Figs 1, 2, 3, 4 and S1. by Carla Maia (349844)

Forecasts of cancer patients’ medical use and expenditure (income/admission cases). by Jinah Sim (15140709)

Forecasts of cancer patients’ medical use and expenditure (income/outpatient cases). by Jinah Sim (15140709)

<i>Effective reproduction number</i> (<i>R</i>_<i>t</i>) for Covid-19 in Brazil. by Hélder Seixas Lima (18840636)

<i>Stay-at-home index</i> (Δ_<i>H</i>) reported for the Brazilian population during the Covid-19 pandemic. by Hélder Seixas Lima (18840636)

SIRDS model simulations across three years for different basic reproduction numbers (<i>R</i>₀). by Hélder Seixas Lima (18840636)

Sensitivity analysis heatmap for perturbations of 1%, 10%, and 50% in optimized parameters with Covid-19 data in Brazil. by Hélder Seixas Lima (18840636)

Effective reproduction number (<i>R</i>_<i>t</i>) for Spain, the United Kingdom, and the United States. by Hélder Seixas Lima (18840636)

Comparative boxplots of effective reproduction number (<i>R</i>_<i>t</i>) similarity distributions in synthetic SIRDS outbreaks. by Hélder Seixas Lima (18840636)

Forecasting Covid-19 dynamics in Brazil for different outbreaks. by Hélder Seixas Lima (18840636)

Comprehensive analysis of simulation results for Covid-19 in Brazil. by Hélder Seixas Lima (18840636)

Summary of Covid-19 data in Brazil (2020–2022). by Hélder Seixas Lima (18840636)

“…We employed a novel Susceptible-Infected-Recovered-Dead-Susceptible (SIRDS) model with a fuzzy transition between epidemic periods to estimate time-varying parameters and evaluate case underreporting. The initial basic reproduction number (<i>R</i>₀) is identified at 2.44 (95% Confidence Interval (CI): 2.42–2.46), decreasing to 1.00 (95% CI: 0.99–1.01) during the first wave. …”

Time-varying model parameters fitted for Covid-19 in Brazil. by Hélder Seixas Lima (18840636)

Forecasting Covid-19 dynamics during the initial outbreak in Brazil. by Hélder Seixas Lima (18840636)

Scenarios. by Maria L. Daza–Torres (12568896)

Spatial model. by Tuan Anh Nguyen (121944)

Illustration of the Susceptible-Infected-Recovered-Dead-Susceptible (SIRDS) model. by Hélder Seixas Lima (18840636)

Model parameter bounds for optimization. by Hélder Seixas Lima (18840636)

“…We employed a novel Susceptible-Infected-Recovered-Dead-Susceptible (SIRDS) model with a fuzzy transition between epidemic periods to estimate time-varying parameters and evaluate case underreporting. The initial basic reproduction number (<i>R</i>₀) is identified at 2.44 (95% Confidence Interval (CI): 2.42–2.46), decreasing to 1.00 (95% CI: 0.99–1.01) during the first wave. …”