Increases in alert level and improved border measures resulted in decreases in secondary transmissions. by Alex James (2916851)

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)

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Effect of parameter <i>a</i> on the model equations by increasing and decreasing value of <i>a</i> to 25%. by Shakoor Ahmad (168711)

“…<p><b>(a)</b> By increasing the value ‘<i>a</i>’ from 0.107 to 0.134. <b>(b)</b> By decreasing the value ‘<i>a</i>’ from 0.107 to 0.08.…”

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

“…Variables in the model are held constant, unless otherwise stated, at values of: a baseline silicosis prevalence of 2%, an increased odds of 1.3 of silicosis per 1 mg/m³-year increase in RCS exposure, a baseline TB incidence of 200 cases per 100,000 per year, an increased odds of 1.05 of TB per 1 mg/m³-year increase in RCS exposure, an increased odds of TB of 4x in those with silicosis, a randomly distributed baseline prevalence of HIV of 2% and an increased odds of TB of 4x in those with HIV. …”

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

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Forecasts of cancer patients’ medical use (cancer type/cases). by Jinah Sim (15140709)

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Forecasts of cancer patients’ medical use (cancer type/cases). by Jinah Sim (15140709)

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

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

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

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Age of patients according to the leishmaniasis clinical form in metropolitan France (n = 509; 8 missing data); red, mean ± standard deviation. by Grégoire Pasquier (3317223)

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GO analysis of stage-salient genes in the order of decreasing significance (i.e, increasing p–value). by Sangeetha Muthamilselvan (8966006)

“…<p>GO analysis of stage-salient genes in the order of decreasing significance (i.e, increasing p–value).</p>…”

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

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Distribution of the endemic leishmaniasis cases reported in metropolitan France by <i>département (i</i>.<i>e</i>. by Grégoire Pasquier (3317223)

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Shows for fifty representative countries the predicted regression of the reciprocal of the rate of increase of the log of confirmed cases (CT^-1) vs the median minimal temperature. by Adam Kaplin (10156481)

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

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<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)

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Distribution of <i>Leishmania</i> species according to the place of transmission from 1998 to 2020). by Grégoire Pasquier (3317223)

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Estimation and prediction of the incidence <i>I</i>(<i>t</i>) in synthetic data. by Oscar Fajardo-Fontiveros (20469421)

“…<p>We consider four simulated epidemic scenarios: (a-d) decreasing incidence after a peak; (e-h) increasing incidence leading to a peak; (i-l) a complete wave; and (m-p) two consecutive waves. …”

The database of the COVID-19 cases in Zhejiang Province. by Haocheng Wu (559031)

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