Inference on spatiotemporal dynamics for coupled biological populations.

Mathematical models in ecology and epidemiology must be consistent with observed data in order to generate reliable knowledge and evidence-based policy. Metapopulation systems, which consist of a network of connected sub-populations, pose technical challenges in statistical inference owing to nonlinear, stochastic interactions. Numerical difficulties encountered in conducting inference can obstruct the core scientific questions concerning the link between the mathematical models and the data.

EXACT PHYLODYNAMIC LIKELIHOOD VIA STRUCTURED MARKOV GENEALOGY PROCESSES.

We consider genealogies arising from a Markov population process in which individuals are categorized into a discrete collection of compartments, with the requirement that individuals within the same compartment are statistically exchangeable. When equipped with a sampling process, each such population process induces a time-evolving tree-valued process defined as the genealogy of all sampled individuals. We provide a construction of this genealogy process and derive exact expressions for the likelihood of an observed genealogy in terms of filter equations.

Informing policy via dynamic models: Cholera in Haiti.

Public health decisions must be made about when and how to implement interventions to control an infectious disease epidemic. These decisions should be informed by data on the epidemic as well as current understanding about the transmission dynamics. Such decisions can be posed as statistical questions about scientifically motivated dynamic models.

Bagged filters for partially observed interacting systems.

Bagging (i.e., bootstrap aggregating) involves combining an ensemble of bootstrap estimators.

Markov genealogy processes.

We construct a family of genealogy-valued Markov processes that are induced by a continuous-time Markov population process. We derive exact expressions for the likelihood of a given genealogy conditional on the history of the underlying population process. These lead to a nonlinear filtering equation which can be used to design efficient Monte Carlo inference algorithms.

Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter.

We propose a method for inference on moderately high-dimensional, nonlinear, non-Gaussian, partially observed Markov process models for which the transition density is not analytically tractable. Markov processes with intractable transition densities arise in models defined implicitly by simulation algorithms. Widely used particle filter methods are applicable to nonlinear, non-Gaussian models but suffer from the curse of dimensionality.

Effect of childhood rotavirus vaccination on community rotavirus prevalence in rural Ecuador, 2008-13.

Background: Although live attenuated monovalent human rotavirus vaccine (Rotarix) efficacy has been characterized through randomized studies, its effectiveness, especially in non-clinical settings, is less clear. In this study, we estimate the impact of childhood Rotarix® vaccination on community rotavirus prevalence.

Methods: We analyse 10 years of serial population-based diarrhoea case-control study, which also included testing for rotavirus infection (n = 3430), and 29 months of all-cause diarrhoea active surveillance from a child cohort (n = 376) from rural Ecuador during a period in which Rotarix vaccination was introduced.

Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns: Micro-Randomized Trial.

Background: Individuals in stressful work environments often experience mental health issues, such as depression. Reducing depression rates is difficult because of persistently stressful work environments and inadequate time or resources to access traditional mental health care services. Mobile health (mHealth) interventions provide an opportunity to deliver real-time interventions in the real world.

Panel Data Analysis via Mechanistic Models.

Panel data, also known as longitudinal data, consist of a collection of time series. Each time series, which could itself be multivariate, comprises a sequence of measurements taken on a distinct unit. Mechanistic modeling involves writing down scientifically motivated equations describing the collection of dynamic systems giving rise to the observations on each unit.

Cardiovascular Risk Factors, Depression, and Alcohol Consumption During Joblessness and During Recessions Among Young Adults in CARDIA.

Research has shown that recessions are associated with lower cardiovascular mortality, but unemployed individuals have a higher risk of cardiovascular disease (CVD) or death. We used data from 8 consecutive examinations (1985-2011) of the Coronary Artery Risk Development in Young Adults (CARDIA) cohort, modeled in fixed-effect panel regressions, to investigate simultaneously the associations of CVD risk factors with the employment status of individuals and the macroeconomic conditions prevalent in the state where the individual lives. We found that unemployed individuals had lower levels of blood pressure, high-density lipoprotein cholesterol, and physical activity, and they had significantly higher depression scores, but they were similar to their counterparts in smoking status, alcohol consumption, low-density lipoprotein cholesterol levels, body mass index, and waist circumference.

A second-order iterated smoothing algorithm.

Simulation-based inference for partially observed stochastic dynamic models is currently receiving much attention due to the fact that direct computation of the likelihood is not possible in many practical situations. Iterated filtering methodologies enable maximization of the likelihood function using simulation-based sequential Monte Carlo filters. Doucet et al.

Population health and the economy: Mortality and the Great Recession in Europe.

We analyze the evolution of mortality-based health indicators in 27 European countries before and after the start of the Great Recession. We find that in the countries where the crisis has been particularly severe, mortality reductions in 2007-2010 were considerably bigger than in 2004-2007. Panel models adjusted for space-invariant and time-invariant factors show that an increase of 1 percentage point in the national unemployment rate is associated with a reduction of 0.

Inference for dynamic and latent variable models via iterated, perturbed Bayes maps.

Iterated filtering algorithms are stochastic optimization procedures for latent variable models that recursively combine parameter perturbations with latent variable reconstruction. Previously, theoretical support for these algorithms has been based on the use of conditional moments of perturbed parameters to approximate derivatives of the log likelihood function. Here, a theoretical approach is introduced based on the convergence of an iterated Bayes map.

Insecticide-treated net use before and after mass distribution in a fishing community along Lake Victoria, Kenya: successes and unavoidable pitfalls.

Background: Insecticide-treated nets (ITNs) have proven instrumental in the successful reduction of malaria incidence in holoendemic regions during the past decade. As distribution of ITNs throughout sub-Saharan Africa (SSA) is being scaled up, maintaining maximal levels of coverage will be necessary to sustain current gains. The effectiveness of mass distribution of ITNs, requires careful analysis of successes and failures if impacts are to be sustained over the long term.

Individual joblessness, contextual unemployment, and mortality risk.

Longitudinal studies at the level of individuals find that employees who lose their jobs are at increased risk of death. However, analyses of aggregate data find that as unemployment rates increase during recessions, population mortality actually declines. We addressed this paradox by using data from the US Department of Labor and annual survey data (1979-1997) from a nationally representative longitudinal study of individuals-the Panel Study of Income Dynamics.

Macroeconomic effects on mortality revealed by panel analysis with nonlinear trends.

Many investigations have used panel methods to study the relationships between fluctuations in economic activity and mortality. A broad consensus has emerged on the overall procyclical nature of mortality: perhaps counter-intuitively, mortality typically rises above its trend during expansions. This consensus has been tarnished by inconsistent reports on the specific age groups and mortality causes involved.

Successes and shortcomings of polio eradication: a transmission modeling analysis.

Polio eradication is on the cusp of success, with only a few regions still maintaining transmission. Improving our understanding of why some regions have been successful and others have not will help with both global eradication of polio and development of more effective vaccination strategies for other pathogens. To examine the past 25 years of eradication efforts, we constructed a transmission model for wild poliovirus that incorporates waning immunity (which affects both infection risk and transmissibility of any resulting infection), age-mediated vaccination rates, and transmission of oral polio vaccine.

The potential elimination of Plasmodium vivax malaria by relapse treatment: insights from a transmission model and surveillance data from NW India.

Background: With over a hundred million annual infections and rising morbidity and mortality, Plasmodium vivax malaria remains largely a neglected disease. In particular, the dependence of this malaria species on relapses and the potential significance of the dormant stage as a therapeutic target, are poorly understood.

Methodology/principal Findings: To quantify relapse parameters and assess the population-wide consequences of anti-relapse treatment, we formulated a transmission model for P.

Cross-correlation map analyses show weather variation influences on mosquito abundance patterns in Saginaw County, Michigan, 1989-2005.

Weather is important determinant of mosquito abundance that, in turn, influences vectorborne disease dynamics. In temperate regions, transmission generally is seasonal as mosquito abundance and behavior varies with temperature, precipitation, and other meteorological factors. We investigated how such factors affected species-specific mosquito abundance patterns in Saginaw County, MI, during a 17-yr period.

A dynamic dose-response model to account for exposure patterns in risk assessment: a case study in inhalation anthrax.

The most commonly used dose-response models implicitly assume that accumulation of dose is a time-independent process where each pathogen has a fixed risk of initiating infection. Immune particle neutralization of pathogens, however, may create strong time dependence; i.e.

Forcing versus feedback: epidemic malaria and monsoon rains in northwest India.

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs.

Plug-and-play inference for disease dynamics: measles in large and small populations as a case study.

Statistical inference for mechanistic models of partially observed dynamic systems is an active area of research. Most existing inference methods place substantial restrictions upon the form of models that can be fitted and hence upon the nature of the scientific hypotheses that can be entertained and the data that can be used to evaluate them. In contrast, the so-called plug-and-play methods require only simulations from a model and are thus free of such restrictions.

Forecasting models of emergency department crowding.

Objectives: The authors investigated whether models using time series methods can generate accurate short-term forecasts of emergency department (ED) bed occupancy, using traditional historical averages models as comparison.

Methods: From July 2005 through June 2006, retrospective hourly ED bed occupancy values were collected from three tertiary care hospitals. Three models of ED bed occupancy were developed for each site: 1) hourly historical average, 2) seasonal autoregressive integrated moving average (ARIMA), and 3) sinusoidal with an autoregression (AR)-structured error term.

Inapparent infections and cholera dynamics.

In many infectious diseases, an unknown fraction of infections produce symptoms mild enough to go unrecorded, a fact that can seriously compromise the interpretation of epidemiological records. This is true for cholera, a pandemic bacterial disease, where estimates of the ratio of asymptomatic to symptomatic infections have ranged from 3 to 100 (refs 1-5). In the absence of direct evidence, understanding of fundamental aspects of cholera transmission, immunology and control has been based on assumptions about this ratio and about the immunological consequences of inapparent infections.