The importance of saturating density dependence for population-level predictions of SARS-CoV-2 resurgence compared with density-independent or linearly density-dependent models,  England, 23 March to 31 July 2020

Background Population-level mathematical models of outbreaks typically assume that disease transmission is not impacted by population density (‘frequency-dependent’) or that it increases linearly with density (‘density-dependent’). Aim We sought evidence for the role of population density in SARS-CoV-2 transmission. Methods Using COVID-19-associated mortality data from England, we fitted multiple functional forms linking density with transmission. We projected forwards beyond lockdown to ascertain the consequences of different functional forms on infection resurgence. Results COVID-19-associated mortality data from England show evidence of increasing with population density until a saturating level, after adjusting for local age distribution, deprivation, proportion of ethnic minority population and proportion of key workers among the working population. Projections from a mathematical model that accounts for this observation deviate markedly from the current status quo for SARS-CoV-2 models which either assume linearity between density and transmission (30% of models) or no relationship at all (70%). Respectively, these classical model structures over- and underestimate the delay in infection resurgence following the release of lockdown. Conclusion Identifying saturation points for given populations and including transmission terms that account for this feature will improve model accuracy and utility for the current and future pandemics.

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The importance of saturating density dependence for predicting SARS-CoV-2 resurgence

10.1101/2020.08.28.20183921 ◽

2020 ◽

Cited By ~ 1

Author(s):

Emily Nightingale ◽

Oliver J Brady ◽

Laith Yakob ◽

Keyword(s):

Age Distribution ◽

Population Projections ◽

Current Status ◽

Mortality Data ◽

Minority Population ◽

Ethnic Minority Population ◽

Improve Model ◽

Increasing Trend ◽

Show Evidence ◽

Model Structures

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) associated mortality data from England show evidence for an increasing trend with population density until a saturating level, after adjusting for local age distribution, deprivation, proportion of ethnic minority population and proportion of key workers among the working population. Projections from a mathematical model that accounts for this observation deviate markedly from the current status quo for SARS-CoV-2 models which either assume linearity between density and transmission (30% of models) or no relationship at all (70%). Respectively, these standard model structures over- and under-estimate the delay in infection resurgence following the release of lockdown. Identifying saturation points for given populations and including transmission terms that account for this feature will improve model accuracy and utility for the current and future pandemics.

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Racial and Ethnic Disparities in Population Level Covid-19 Mortality

10.1101/2020.05.07.20094250 ◽

2020 ◽

Cited By ~ 20

Author(s):

Cary P. Gross ◽

Utibe R. Essien ◽

Saamir Pasha ◽

Jacob R Gross ◽

Shi-yi Wang ◽

...

Keyword(s):

Race And Ethnicity ◽

Age Distribution ◽

Ethnic Disparities ◽

Population Level ◽

The United States ◽

Mortality Data ◽

Population Groups ◽

Risk Of Death ◽

Mortality Disparities ◽

Ethnicity Data

AbstractBackgroundCurrent reporting of Covid-19 mortality data by race and ethnicity across the United States could bias our understanding of population-mortality disparities. Moreover, stark differences in age distribution by race and ethnicity groups are seldom accounted for in analyses.MethodsTo address these gaps, we conducted a cross-sectional study using publicly-reported Covid-19 mortality data to assess the quality of race and ethnicity data (Black, Latinx, white), and estimated age-adjusted disparities using a random effects meta-analytic approach.ResultsWe found only 28 states, and NYC, reported race and ethnicity-stratified Covid-19 mortality along with large variation in the percent of missing race and ethnicity data by state. Aggregated relative risk of death estimates for Black compared to the white population was 3.57 (95% CI: 2.84-4.48). Similarly, Latinx population displayed 1.88 (95% CI: 1.61-2.19) times higher risk of death than white patients.DiscussionIn states providing race and ethnicity data, we identified significant population-level Covid-19 mortality disparities. We demonstrated the importance of adjusting for age differences across population groups to prevent underestimating disparities in younger population groups. The availability of high-quality and comprehensive race and ethnicity data is necessary to address factors contributing to inequity in Covid-19 mortality.

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Faculty Opinions recommendation of Population density-dependent regulation of exopolysaccharide formation in the hyperthermophilic bacterium Thermotoga maritima.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1026992.327523 ◽

2005 ◽

Author(s):

Camilla Nesbø

Keyword(s):

Population Density ◽

Thermotoga Maritima ◽

Density Dependent ◽

Hyperthermophilic Bacterium ◽

Density Dependent Regulation

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Sexual minority population density and incidence of lung, colorectal and female breast cancer in California

BMJ Open ◽

10.1136/bmjopen-2013-004461 ◽

2014 ◽

Vol 4 (3) ◽

pp. e004461 ◽

Cited By ~ 15

Author(s):

Ulrike Boehmer ◽

Xiaopeng Miao ◽

Nancy I Maxwell ◽

Al Ozonoff

Keyword(s):

Breast Cancer ◽

Population Density ◽

Sexual Minority ◽

Female Breast Cancer ◽

Minority Population ◽

Female Breast

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The Role of Respiratory Infection in Sudden Infant Death Syndrome (SIDS)

Scandinavian Journal of Forensic Science ◽

10.1515/sjfs-2016-0004 ◽

2016 ◽

Vol 22 (1) ◽

pp. 15-20 ◽

Cited By ~ 1

Author(s):

David T. Mage ◽

Maria L. Latorre ◽

Alejandro G. Jenik ◽

E. Maria Donner

Keyword(s):

Birth Order ◽

Respiratory Infection ◽

Live Birth ◽

Sudden Infant Death Syndrome ◽

Infant Death ◽

Age Distribution ◽

Sudden Infant Death ◽

Physiological Model ◽

Mortality Data ◽

Sudden Infant

Abstract Introduction: The Sudden Infant Death Syndrome (SIDS) is not likely to be explained by a currently measureable presence in all cases and absence in controls, as otherwise it would have been solved already. Indeed, any proposed physiological model for SIDS causation must explain the constant mathematical and statistical properties of SIDS age and gender. We have shown previously that SIDS are characterized by a common 4-parameter lognormal age distribution sparing neonatal infants, by a nominal 50% male excess, and by a higher rate in winter than summer. We test now whether SIDS is closely related to a fulminating prodromal Acute Respiratory Infection (ARI) by a common increasing rate with the infants increasing Live Birth Order (LBO), all remaining the same, independent of the change in preferred sleeping positions of the infants, prone or supine. Methods: We use U.S. published infant mortality data from wonder.cdc.gov and other countries (Colombia, U.K., Europe, Australasia) to make comparisons between the two causes of death (ARI and SIDS) to evaluate how closely ARI resembles the characteristics of SIDS. Results: Gender: SIDS male excess 50%, ARI male excess 50%; Ages: SIDS 90% post-neonatal, ARI 96% post-neonatal; Seasonality: SIDS and ARI are higher in winter than summer; Live birth order: SIDS and ARI rates increase with increasing LBO with similar mathematical relationship. Conclusion: Our results show that all SIDS are very likely relatable to a single cause tied to a fulminating prodromal ARI in a physiologically anemic infant who is genetically (X-link recessive) susceptible to cerebral anoxia. An alternative cause of all SIDS death by a collection of subsets of different causes, such as brainstem-related respiratory abnormalities and cardiac QT abnormalities, is not supported because they cannot all have the same age-gender-seasonal-familial-distributions of SIDS, required by Cramér’s Theorem.

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Correlated gamma frailty models for bivariate survival time data

Statistical Methods in Medical Research ◽

10.1177/0962280218803127 ◽

2018 ◽

Vol 28 (10-11) ◽

pp. 3437-3450

Author(s):

Adelino Martins ◽

Marc Aerts ◽

Niel Hens ◽

Andreas Wienke ◽

Steven Abrams

Keyword(s):

Survival Time ◽

Frailty Models ◽

Current Status Data ◽

Current Status ◽

Mortality Data ◽

Time Data ◽

Additive Decomposition ◽

Bivariate Survival ◽

Gamma Frailty ◽

Survival Time Data

Frailty models have been developed to quantify both heterogeneity as well as association in multivariate time-to-event data. In recent years, numerous shared and correlated frailty models have been proposed in the survival literature allowing for different association structures and frailty distributions. A bivariate correlated gamma frailty model with an additive decomposition of the frailty variables into a sum of independent gamma components was introduced before. Although this model has a very convenient closed-form representation for the bivariate survival function, the correlation among event- or subject-specific frailties is bounded above which becomes a severe limitation when the values of the two frailty variances differ substantially. In this article, we review existing correlated gamma frailty models and propose novel ones based on bivariate gamma frailty distributions. Such models are found to be useful for the analysis of bivariate survival time data regardless of the censoring type involved. The frailty methodology was applied to right-censored and left-truncated Danish twins mortality data and serological survey current status data on varicella zoster virus and parvovirus B19 infections in Belgium. From our analyses, it has been shown that fitting more flexible correlated gamma frailty models in terms of the imposed association and correlation structure outperforms existing frailty models including the one with an additive decomposition.

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Moving towards a reliable HIV incidence test – current status, resources available, future directions and challenges ahead

Epidemiology and Infection ◽

10.1017/s0950268816002910 ◽

2016 ◽

Vol 145 (5) ◽

pp. 925-941 ◽

Cited By ~ 19

Author(s):

G. MURPHY ◽

C. D. PILCHER ◽

S. M. KEATING ◽

R. KASSANJEE ◽

S. N. FACENTE ◽

...

Keyword(s):

Performance Metrics ◽

Critical Path ◽

Population Level ◽

Current Status ◽

Hiv Incidence ◽

Recent Infection ◽

Novel Approach ◽

Product Profile ◽

And Performance ◽

The Impact

SUMMARYIn 2011 the Incidence Assay Critical Path Working Group reviewed the current state of HIV incidence assays and helped to determine a critical path to the introduction of an HIV incidence assay. At that time the Consortium for Evaluation and Performance of HIV Incidence Assays (CEPHIA) was formed to spur progress and raise standards among assay developers, scientists and laboratories involved in HIV incidence measurement and to structure and conduct a direct independent comparative evaluation of the performance of 10 existing HIV incidence assays, to be considered singly and in combinations as recent infection test algorithms. In this paper we report on a new framework for HIV incidence assay evaluation that has emerged from this effort over the past 5 years, which includes a preliminary target product profile for an incidence assay, a consensus around key performance metrics along with analytical tools and deployment of a standardized approach for incidence assay evaluation. The specimen panels for this evaluation have been collected in large volumes, characterized using a novel approach for infection dating rules and assembled into panels designed to assess the impact of important sources of measurement error with incidence assays such as viral subtype, elite host control of viraemia and antiretroviral treatment. We present the specific rationale for several of these innovations, and discuss important resources for assay developers and researchers that have recently become available. Finally, we summarize the key remaining steps on the path to development and implementation of reliable assays for monitoring HIV incidence at a population level.

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Density-Dependent Population Growth

Fishery Ecosystem Dynamics ◽

10.1093/oso/9780198768937.003.0003 ◽

2020 ◽

pp. 29-46

Author(s):

Michael J. Fogarty ◽

Jeremy S. Collie

Keyword(s):

Population Density ◽

Population Growth ◽

Density Dependence ◽

Multiple Equilibria ◽

Dynamical Behavior ◽

Logistic Growth ◽

Density Dependent ◽

Per Capita ◽

Discrete Time Models ◽

Complex Dynamical Behavior

The observation that no population can grow indefinitely and that most populations persist on ecological timescales implies that mechanisms of population regulation exist. Feedback mechanisms include competition for limited resources, cannibalism, and predation rates that vary with density. Density dependence occurs when per capita birth or death rates depend on population density. Density dependence is compensatory when the population growth rate decreases with population density and depensatory when it increases. The logistic model incorporates density dependence as a simple linear function. A population exhibiting logistic growth will reach a stable population size. Non-linear density-dependent terms can give rise to multiple equilibria. With discrete time models or time delays in density-dependent regulation, the approach to equilibrium may not be smooth—complex dynamical behavior is possible. Density-dependent feedback processes can compensate, up to a point, for natural and anthropogenic disturbances; beyond this point a population will collapse.

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Introduction to pertussis transmission and epidemiological dynamics

Pertussis ◽

10.1093/oso/9780198811879.003.0001 ◽

2018 ◽

pp. 6-25

Author(s):

Pejman Rohani ◽

Samuel V. Scarpino

Keyword(s):

Control Strategies ◽

Age Distribution ◽

Population Level ◽

Vaccine Uptake ◽

Effective Control ◽

Transmission Potential ◽

Epidemic Period ◽

The Impact ◽

Pertussis Epidemiology

Resolving the long-term, population-level consequences of changes in pertussis epidemiology, arising from bacterial evolution, shifts in vaccine-induced immunity, or changes in surveillance, are key challenges for devising effective control strategies. This chapter reviews some of the key features of pertussis epidemiology, together with the underlying epidemiological principles that set the context for their interpretation. These include the relationship between the age distribution of cases and pertussis transmission potential, the impact of vaccine uptake on incidence, periodicity and age incidence, as well as spatially explicit recurrent pertussis epidemics and associated extinction frequency. This review highlights some of the predictable and consistent aspects of pertussis epidemiology (e.g. the systematic increase in the inter-epidemic period with the introduction of whole-cell vaccines) and a number of important heterogeneities, including variations in contemporary patterns of incidence and geographic spread.

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