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

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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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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Daily confirmed COVID-19 cases (n = 61,993) and smoothed trends for the median age of all the cases, hospitalized cases, and deceased cases. by Diego Casas-Deza (11819838)

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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.…”

Population infected in case of increase in susceptibility. by Juliano Genari (13794299)

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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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Temporal distribution of COVID-19 confirmed cases: Hospitalised cases and deaths. by Imelda Sonia Nzinnou Mbiaketcha (14670572)

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Reduced contact tracing efficiency with increasing cases leads to accelerating epidemics. by Billy J. Gardner (10988034)

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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>…”

Spread of COVID-19 (difference in cases, rate increase, incremental rate increase, and transmission rate β by province). by Alessandra Buja (535536)

“…<p>Spread of COVID-19 (difference in cases, rate increase, incremental rate increase, and transmission rate β by province).…”

Daily COVID-19 case residuals. by Jack Sutton (9411465)

Largest twenty coefficients by absolute value as defined by logistic regression. by Roshan Karri (11060943)

“…Negative values signify that as the variable decreases, the risk of requiring invasive ventilation decreases. …”