Benjamin M Bolker
Datos Biográficos
| ID | 3429458 |
|---|---|
| NOMBRE | Benjamin M Bolker |
| NOMBRES | Benjamin M |
| APELLIDO | Bolker |
| FIRMA | BOLKER B M |
| AFILIACIONES | McMaster University |
| ORCID | 0000-0002-2127-0443 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 5 |
| TOTAL DE CITAS | 0 |
| OBRAS COMO AUTOR | 5 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2015 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 0 |
A century of weekly notifiable disease incidence data by province in Canada
Canadian notifiable disease surveillance programmes have recorded communicable disease incidence data, dating back to the late 19th century. A Public Health Agency of Canada web-portal provides summaries of these data from 1924–2023, but lacks details on how incidence varies seasonally and geographically among provinces. The sub-annual (weekly, monthly, quarterly) and sub-national (provincial, territorial) data required to study such patterns app…
Age-dependence of healthcare interventions for Covid-19 in Ontario, Canada
Our study demonstrates a significant need for hospitalization in middle-aged individuals and young seniors. This need is not captured by the distribution of deaths, which is heavily concentrated in very old ages. The probability of survival given hospitalization for COVID-19 is lower than is generally perceived for patients over 40. If acute care capacity is exceeded due to an increase in COVID-19 prevalence, the distribution of deaths could expa…
Patterns of seasonal and pandemic influenza-associated health care and mortality in Ontario, Canada
Our empirical delay distributions and conditional probabilities should help facilitate more accurate forecasts in the future, including improved predictions of hospital bed demands during influenza outbreaks, and the expected effects of hospitalizations on epidemic dynamics
Fitting Linear Mixed-Effects Models Using lme4
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled dev…
Moving Beyond Too Little, Too Late
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Fitting Linear Mixed-Effects Models Using lme4
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled dev…
Moving Beyond Too Little, Too Late
Patterns of seasonal and pandemic influenza-associated health care and mortality in Ontario, Canada
Our empirical delay distributions and conditional probabilities should help facilitate more accurate forecasts in the future, including improved predictions of hospital bed demands during influenza outbreaks, and the expected effects of hospitalizations on epidemic dynamics
Age-dependence of healthcare interventions for Covid-19 in Ontario, Canada
Our study demonstrates a significant need for hospitalization in middle-aged individuals and young seniors. This need is not captured by the distribution of deaths, which is heavily concentrated in very old ages. The probability of survival given hospitalization for COVID-19 is lower than is generally perceived for patients over 40. If acute care capacity is exceeded due to an increase in COVID-19 prevalence, the distribution of deaths could expa…
A century of weekly notifiable disease incidence data by province in Canada
Canadian notifiable disease surveillance programmes have recorded communicable disease incidence data, dating back to the late 19th century. A Public Health Agency of Canada web-portal provides summaries of these data from 1924–2023, but lacks details on how incidence varies seasonally and geographically among provinces. The sub-annual (weekly, monthly, quarterly) and sub-national (provincial, territorial) data required to study such patterns app…
Public health (4 obras) · Disease (3 obras) · Medicine (3 obras) · Biostatistics (2 obras) · Coronavirus disease 2019 (COVID-19 (2 obras) · COVID-19 epidemiological studies (2 obras) · Demography (2 obras) · Demography (2 obras) · Emergency Medicine (2 obras) · Epidemiology (2 obras)