The DIOS framework for optimizing infectious disease surveillance: Numerical methods for simulation and multi-objective optimization of surveillance network architectures.

Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters-such as the number and placement of surveillance sites, target populations, and case definitions-are often determined by expert opinion or deference to operational considerations, without formal analysis of the influence of design parameters on surveillance objectives. Here we propose a simulation framework to guide evidence-based surveillance network design to better achieve specific surveillance goals with limited resources. We define evidence-based surveillance design as an optimization problem, acknowledging the many operational constraints under which surveillance systems operate, the many dimensions of surveillance system design, the multiple and competing goals of surveillance, and the complex and dynamic nature of disease systems. We describe an analytical framework-the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework-for the identification of optimal surveillance designs through mathematical representations of disease and surveillance processes, definition of objective functions, and numerical optimization. We then apply the framework to the problem of selecting candidate sites to expand an existing surveillance network under alternative objectives of: (1) improving spatial prediction of disease prevalence at unmonitored sites; or (2) estimating the observed effect of a risk factor on disease. Results of this demonstration illustrate how optimal designs are sensitive to both surveillance goals and the underlying spatial pattern of the target disease. The findings affirm the value of designing surveillance systems through quantitative and adaptive analysis of network characteristics and performance. The framework can be applied to the design of surveillance systems tailored to setting-specific disease transmission dynamics and surveillance needs, and can yield improved understanding of tradeoffs between network architectures.

Prenatal and early-life exposure to the Great Chinese Famine increased the risk of tuberculosis in adulthood across two generations.

Global food security is a major driver of population health, and food system collapse may have complex and long-lasting effects on health outcomes. We examined the effect of prenatal exposure to the Great Chinese Famine (1958-1962)-the largest famine in human history-on pulmonary tuberculosis (PTB) across consecutive generations in a major center of ongoing transmission in China. We analyzed >1 million PTB cases diagnosed between 2005 and 2018 in Sichuan Province using age-period-cohort analysis and mixed-effects metaregression to estimate the effect of the famine on PTB risk in the directly affected birth cohort (F1) and their likely offspring (F2). The analysis was repeated on certain sexually transmitted and blood-borne infections (STBBI) to explore potential mechanisms of the intergenerational effects. A substantial burden of active PTB in the exposed F1 cohort and their offspring was attributable to the Great Chinese Famine, with more than 12,000 famine-attributable active PTB cases (>1.23% of all cases reported between 2005 and 2018). An interquartile range increase in famine intensity resulted in a 6.53% (95% confidence interval [CI]: 1.19-12.14%) increase in the ratio of observed to expected incidence rate (incidence rate ratio, IRR) in the absence of famine in F1, and an 8.32% (95% CI: 0.59-16.6%) increase in F2 IRR. Increased risk of STBBI was also observed in F2. Prenatal and early-life exposure to malnutrition may increase the risk of active PTB in the exposed generation and their offspring, with the intergenerational effect potentially due to both within-household transmission and increases in host susceptibility.

The Impact of Vaccination Efforts on the Spatiotemporal Patterns of the Hepatitis A Outbreak in Michigan, 2016-2018.

BACKGROUND: The United States is currently experiencing the largest hepatitis A virus (HAV) outbreak since the introduction of a vaccine in 1996. More than 31,000 cases have been reported since 2016. Although HAV had largely been considered a foodborne pathogen in recent years, this outbreak has been spread primarily through person-to-person transmission in urban settings and has been associated with homelessness and substance use. Michigan was one of the first states to report an outbreak, with 910 reported cases between August 2016 and December 2018. METHODS: We analyzed surveillance and vaccination data from Michigan using a disease transmission model to investigate how vaccine timing and coverage influenced the spatiotemporal patterns of the outbreak, distinguishing between Southeast Michigan, where the outbreak began, and the rest of the state. RESULTS: We estimated that vaccination had little impact in Southeast Michigan (3% cases averted [95% confidence interval (CI) = 1%, 8%]) but had a substantial impact in the rest of the state, preventing a larger outbreak (91% cases averted [95% CI = 85%, 97%]) lasting several more years. CONCLUSIONS: Our results emphasize the value of targeting populations where local transmission is not yet sustained rather than populations where transmission is already waning. Simulation modeling can aid in proactive rather than reactive decision-making and may help direct the response to outbreaks emerging in other states. See video abstract: http://links.lww.com/EDE/B704.

Evidence for heterogeneity in China's progress against pulmonary tuberculosis: uneven reductions in a major center of ongoing transmission, 2005-2017.

BACKGROUND: China contributed 8.9% of all incident cases of tuberculosis globally in 2017, and understanding the spatiotemporal distribution of pulmonary tuberculosis (PTB) in major transmission foci in the country is critical to ongoing efforts to improve population health. METHODS: We estimated annual PTB notification rates and their spatiotemporal distributions in Sichuan province, a major center of ongoing transmission, from 2005 to 2017. Time series decomposition was used to obtain trend components from the monthly incidence rate time series. Spatiotemporal cluster analyses were conducted to detect spatiotemporal clusters of PTB at the county level. RESULTS: From 2005 to 2017, 976,873 cases of active PTB and 388,739 cases of smear-positive PTB were reported in Sichuan Province, China. During this period, the overall reported incidence rate of active PTB decreased steadily at a rate of decrease (3.77 cases per 100,000 per year, 95% confidence interval (CI): 3.28-4.31) that was slightly faster than the national average rate of decrease (3.14 cases per 100,000 per year, 95% CI: 2.61-3.67). Although reported PTB incidence decreased significantly in most regions of the province, incidence was observed to be increasing in some counties with high HIV incidence and ethnic minority populations. Active and smear-positive PTB case reports exhibited seasonality, peaking in March and April, with apparent links to social dynamics and climatological factors. CONCLUSIONS: While PTB incidence rates decreased strikingly in the study area over the past decade, improvements have not been equally distributed. Additional surveillance and control efforts should be guided by the seasonal-trend and spatiotemporal cluster analyses presented here, focusing on areas with increasing incidence rates, and updated to reflect the latest information from real-time reporting.

Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis.

BACKGROUND: Congregate settings may serve as institutional amplifiers of tuberculosis (TB) and multidrug-resistant tuberculosis (MDR-TB). We analyze spatial, epidemiological, and pathogen genetic data prospectively collected from neighborhoods surrounding a prison in Lima, Peru, where inmates experience a high risk of MDR-TB, to investigate the risk of spillover into the surrounding community. METHODS: Using hierarchical Bayesian statistical modeling, we address three questions regarding the MDR-TB risk: (i) Does the excess risk observed among prisoners also extend outside the prison? (ii) If so, what is the magnitude, shape, and spatial range of this spillover effect? (iii) Is there evidence of additional transmission across the region? RESULTS: The region of spillover risk extends for 5.47 km outside of the prison (95% credible interval: 1.38, 9.63 km). Within this spillover region, we find that nine of the 467 non-inmate patients (35 with MDR-TB) have MDR-TB strains that are genetic matches to strains collected from current inmates with MDR-TB, compared to seven out of 1080 patients (89 with MDR-TB) outside the spillover region (p values: 0.022 and 0.008). We also identify eight spatially aggregated genetic clusters of MDR-TB, four within the spillover region, consistent with local transmission among individuals living close to the prison. CONCLUSIONS: We demonstrate a clear prison spillover effect in this population, which suggests that interventions in the prison may have benefits that extend to the surrounding community.

Identifying Hotspots of Multidrug-Resistant Tuberculosis Transmission Using Spatial and Molecular Genetic Data.

BACKGROUND: We aimed to identify and determine the etiology of "hotspots" of concentrated multidrug-resistant tuberculosis (MDR-tuberculosis) risk in Lima, Peru. METHODS: From 2009 to 2012, we conducted a prospective cohort study among households of tuberculosis cases from 106 health center (HC) areas in Lima, Peru. All notified tuberculosis cases and their household contacts were followed for 1 year. Symptomatic individuals were screened by microscopy and culture; positive cultures were tested for drug susceptibility (DST) and genotyped by 24-loci mycobacterial interspersed repetitive units-variable-number tandem repeats (MIRU-VNTR). RESULTS: 3286 individuals with culture-confirmed disease, DST, and 24-loci MIRU-VNTR were included in our analysis. Our analysis reveals: (1) heterogeneity in annual per-capita incidence of tuberculosis and MDR-tuberculosis by HC, with a rate of MDR-tuberculosis 89 times greater (95% confidence interval [CI], 54,185) in the most-affected versus the least-affected HC; (2) high risk for MDR-tuberculosis in a region spanning several HCs (odds ratio = 3.19, 95% CI, 2.33, 4.36); and (3) spatial aggregation of MDR-tuberculosis genotypes, suggesting localized transmission. CONCLUSIONS: These findings reveal that localized transmission is an important driver of the epidemic of MDR-tuberculosis in Lima. Efforts to interrupt transmission may be most effective if targeted to this area of the city.

Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013-2014.

Morbilliviruses cause major mortality in marine mammals, but the dynamics of transmission and persistence are ill understood compared to terrestrial counterparts such as measles; this is especially true for epidemics in cetaceans. However, the recent outbreak of dolphin morbillivirus in the northwestern Atlantic Ocean can provide new insights into the epidemiology and spatio-temporal spread of this pathogen. To deal with uncertainties surrounding the ecology of this system (only stranded animals were observed), we develop a statistical framework that can extract key information about the underlying transmission process given only sparse data. Our self-exciting Poisson process model suggests that individuals are infectious for at most 24 days and can transfer infection up to two latitude degrees (220 km) within this time. In addition, the effective reproduction number is generally below one, but reaches 2.6 during a period of heightened stranding numbers near Virginia Beach, Virginia, in summer 2013. Network analysis suggests local movements dominate spatial spread, with seasonal migration facilitating wider dissemination along the coast. Finally, a low virus transmission rate or high levels of pre-existing immunity can explain the lack of viral spread into the Gulf of Mexico. More generally, our approach illustrates novel methodologies for analysing very indirectly observed epidemics.

The impact of environmental and climatic variation on the spatiotemporal trends of hospitalized pediatric diarrhea in Ho Chi Minh City, Vietnam.

It is predicted that the integration of climate-based early warning systems into existing action plans will facilitate the timely provision of interventions to diarrheal disease epidemics in resource-poor settings. Diarrhea remains a considerable public health problem in Ho Chi Minh City (HCMC), Vietnam and we aimed to quantify variation in the impact of environmental conditions on diarrheal disease risk across the city. Using all inpatient diarrheal admissions data from three large hospitals within HCMC, we developed a mixed effects regression model to differentiate district-level variation in risk due to environmental conditions from the overarching seasonality of diarrheal disease hospitalization in HCMC. We identified considerable spatial heterogeneity in the risk of all-cause diarrhea across districts of HCMC with low elevation and differential responses to flooding, air temperature, and humidity driving further spatial heterogeneity in diarrheal disease risk. The incorporation of these results into predictive forecasting algorithms will provide a powerful resource to aid diarrheal disease prevention and control practices in HCMC and other similar settings.

Age-specific risks of tuberculosis infection from household and community exposures and opportunities for interventions in a high-burden setting.

We analyzed data from a large population-based prospective cohort study of household contacts of tuberculosis patients in Lima, Peru, to estimate the importance of within-household transmission relative to community-based transmission. We identified all adults (older than 15 years of age) who had incident pulmonary tuberculosis diagnosed at any of 106 public health centers in Lima from September 2009 to August 2012. A total of 14,041 household contacts of 3,446 index patients were assessed for tuberculosis infection and disease. We compared the prevalence of latent tuberculosis infection (LTBI) among persons who had received the Bacillus Calmette-Guérin vaccine in households with and without a microbiologically confirmed index case to estimate the age-specific risk of infection and excess risk of LTBI from household and community exposures. We found that the risk of infection from household and community sources increased from birth until 20 years of age. However, a large proportion of infections among child and young-adult household contacts could have been the result of household exposure. Excess infection risk associated with household exposure accounted for 58% (95% confidence interval: 47, 66) of LTBI prevalence among exposed children younger than 1 year of age, 48% (95% confidence interval: 39, 57) among 10-year-old children, and 44% (95% confidence interval: 34, 51) among 15-year-old adolescents. These findings suggest that expanded access to preventive therapy for older children and young-adult household contacts of known tuberculosis cases may be beneficial.

Bacillus Calmette-Guérin and isoniazid preventive therapy protect contacts of patients with tuberculosis.

RATIONALE: Individuals living with patients with tuberculosis (TB) are at elevated risk of infection and disease, with children at greatest risk. The World Health Organization recommends isoniazid preventive therapy (IPT) for HIV-positive contacts and those younger than 5 years. Despite these recommendations, household-level IPT programs are rarely implemented in high TB burden settings. Evidence is scarce about the age-specific efficacy of interventions, such as IPT and bacillus Calmette-Guérin (BCG) vaccination for preventing TB disease among exposed contacts. OBJECTIVES: We estimate the age-specific efficacy of IPT and BCG for preventing TB disease using data from a large observational prospective cohort study of household contacts of patients with TB in Lima, Peru. METHODS: We identified all adults (>15 yr) with incident pulmonary TB (index cases) diagnosed at 106 public health centers in Lima from September 2009 to August 2012. Among 14,041 household contacts (of 3,446 index cases) assessed for infection and disease during the year-long follow-up period, we identified 462 additional TB cases. We estimate risk ratios (RR) for pulmonary TB associated with BCG, IPT, and latent TB infection. MEASUREMENTS AND MAIN RESULTS: BCG confers protection against coprevalent and incident TB among HIV-negative children younger than 10 years (RR, 0.35; 95% confidence interval, 0.19-0.66). IPT confers protection against incident TB among HIV-negative contacts younger than 30 years (RR, 0.33; 95% confidence interval, 0.20-0.54). Risk of incident TB associated with latent TB infection is greatest for children younger than 5 years and decreases with age. CONCLUSIONS: These findings support the use of IPT in older children and young-adult household contacts, in addition to children younger than 5 years.

Linking time-varying symptomatology and intensity of infectiousness to patterns of norovirus transmission.

BACKGROUND: Norovirus (NoV) transmission may be impacted by changes in symptom intensity. Sudden onset of vomiting, which may cause an initial period of hyper-infectiousness, often marks the beginning of symptoms. This is often followed by: a 1-3 day period of milder symptoms, environmental contamination following vomiting, and post-symptomatic shedding that may result in transmission at progressively lower rates. Existing models have not included time-varying infectiousness, though representing these features could add utility to models of NoV transmission. METHODS: We address this by comparing the fit of three models (Models 1-3) of NoV infection to household transmission data from a 2009 point-source outbreak of GII.12 norovirus in North Carolina. Model 1 is an SEIR compartmental model, modified to allow Gamma-distributed sojourn times in the latent and infectious classes, where symptomatic cases are uniformly infectious over time. Model 2 assumes infectiousness decays exponentially as a function of time since onset, while Model 3 is discontinuous, with a spike concentrating 50% of transmissibility at onset. We use Bayesian data augmentation techniques to estimate transmission parameters for each model, and compare their goodness of fit using qualitative and quantitative model comparison. We also assess the robustness of our findings to asymptomatic infections. RESULTS: We find that Model 3 (initial spike in shedding) best explains the household transmission data, using both quantitative and qualitative model comparisons. We also show that these results are robust to the presence of asymptomatic infections. CONCLUSIONS: Explicitly representing explosive NoV infectiousness at onset should be considered when developing models and interventions to interrupt and prevent outbreaks of norovirus in the community. The methods presented here are generally applicable to the transmission of pathogens that exhibit large variation in transmissibility over an infection.

Social connectedness and disease transmission: social organization, cohesion, village context, and infection risk in rural Ecuador.

Social networks are typically seen as conduits for the spread of disease and disease risk factors. However, social relationships also reduce the incidence of chronic disease and potentially infectious diseases. Seldom are these opposing effects considered simultaneously. We have shown how and why diarrheal disease spreads more slowly to and in rural Ecuadorian villages that are more remote from the area's population center. Reduced contact with outside individuals partially accounts for remote villages' relatively lower prevalence of diarrheal disease. But equally or more important is the greater density of social ties between individuals in remote communities, which facilitates the spread of individual and collective practices that reduce the transmission of diarrheal disease.

How infections propagate after point-source outbreaks: an analysis of secondary norovirus transmission.

BACKGROUND: Secondary transmission after point-source outbreaks is an integral feature of the epidemiology of gastrointestinal pathogens such as norovirus. The household is an important site of these secondary cases. It can become the source of further community transmission as well as new point-source outbreaks. Consequently, time-series data from exposed households provide information for risk assessment and intervention. METHODS: Analysis of these data requires models that can address (1) dependencies in infection transmission, (2) random variability resulting from households with few members, and (3) unobserved state variables important to transmission. We use Monte Carlo maximum likelihood via data augmentation for obtaining estimates of the transmission rate and infectious period from household outbreaks with the 3 above features. RESULTS: We apply this parameter estimation technique to 153 infection sequences within households from a norovirus outbreak in Sweden and obtain maximum likelihood estimates of the daily rate of transmission ([Greek small letter beta with circumflex accent] = 0.14, 95% confidence interval [CI] = 0.08-0.24) and average infectious period (1/[Greek small letter gamma with circumflex accent] = 1.17 days, 95% CI = 1.00-1.88). We also demonstrate the robustness of the estimates to missing household sizes and asymptomatic infections. CONCLUSIONS: Maximum likelihood techniques such as these can be used to estimate transmission parameters under conditions of unobserved states and missing household size data, and to aid in the understanding of secondary risks associated with point-source outbreaks.