Outbreak Durations Research Articles

Missingness and algorithmic bias: an example from the United States National Outbreak Reporting System, 2009-2019.

Growing debates about algorithmic bias in public health surveillance lack specific examples. We tested a common assumption that exposure and illness periods coincide and demonstrated how algorithmic bias can arise due to missingness of critical information related to illness and exposure durations. We examined 9407 outbreaks recorded by the United States National Outbreak Reporting System (NORS) from January 1, 2009 through December 31, 2019 and detected algorithmic bias, a systematic over- or under-estimation of foodborne disease outbreak (FBDO) durations due to missing start and end dates. For 7037 (75%) FBDOs with complete date-time information, ~ 60% reported that the exposure period ended before the illness period started. For 2079 (87.7%) FBDOs with missing exposure dates, average illness durations were ~ 5.3 times longer (p < 0.001) than those with complete information, prompting the potential for algorithmic bias. Modern surveillance systems must be equipped with investigative capacities to examine and assess structural data missingness that can lead to bias.

Systematic review of global hepatitis E outbreaks to inform response and coordination initiatives

IntroductionHepatitis E virus (HEV) is the most common cause of acute hepatitis. While symptoms are generally mild and resolve within weeks, some populations (e.g., pregnant women, immunocompromised adults) are at high-risk of severe HEV-related morbidity and mortality. There has not been a recent comprehensive review of contemporary HEV outbreaks, which limits the validity of current disease burden estimates. Therefore, we aimed to characterize global HEV outbreaks and describe data gaps to inform HEV outbreak prevention and response initiatives.MethodsWe performed a systematic review of peer-reviewed (PubMed, Embase) and gray literature (ProMED) to identify reports of outbreaks published between 2011 and 2022. We included (1) reports with ≥ 5 cases of HEV, and/or (2) reports with 1.5 times the baseline incidence of HEV in a specific population, and (3) all reports with suspected (e.g., clinical case definition) or confirmed (e.g., ELISA or PCR test) cases if they met criterium 1 and/or 2. We describe key outbreak epidemiological, prevention and response characteristics and major data gaps.ResultsWe identified 907 records from PubMed, 468 from Embase, and 247 from ProMED. We screened 1,362 potentially relevant records after deduplication. Seventy-one reports were synthesized, representing 44 HEV outbreaks in 19 countries. The populations at risk, case fatalities, and outbreak durations were not reported in 66% of outbreak reports. No reports described using HEV vaccines. Reported intervention efforts included improving sanitation and hygiene, contact tracing/case surveillance, chlorinating boreholes, and advising residents to boil water. Commonly missing data elements included specific case definitions used, testing strategy and methods, seroprevalence, impacts of interventions, and outbreak response costs. Approximately 20% of HEV outbreaks we found were not published in the peer-reviewed literature.ConclusionHEV represents a significant public health problem. Unfortunately, extensive data shortages and a lack of standardized reporting make it difficult to estimate the HEV disease burden accurately and to implement effective prevention and response activities. Our study has identified major gaps to guide future studies and outbreak reporting systems. Our results support the development of standardized reporting procedures/platforms for HEV outbreaks to ensure accurate and timely data distribution, including active and passive coordinated surveillance systems, particularly among high-risk populations.

Immunologic and Epidemiologic Drivers of Norovirus Transmission in Daycare and School Outbreaks.

Norovirus outbreaks are notoriously explosive, with dramatic symptomology and rapid disease spread. Children are particularly vulnerable to infection and drive norovirus transmission due to their high contact rates with each other and the environment. Despite the explosive nature of norovirus outbreaks, attack rates in schools and daycares remain low with the majority of students not reporting symptoms. We explore immunologic and epidemiologic mechanisms that may underlie epidemic norovirus transmission dynamics using a disease transmission model. Towards this end, we compared different model scenarios, including innate resistance and acquired immunity (collectively denoted 'immunity'), stochastic extinction, and an individual exclusion intervention. We calibrated our model to daycare and school outbreaks from national surveillance data. Including immunity in the model led to attack rates that were consistent with the data. However, immunity alone resulted in the majority of outbreak durations being relatively short. The addition of individual exclusion (to the immunity model) extended outbreak durations by reducing the amount of time that symptomatic people contribute to transmission. Including both immunity and individual exclusion mechanisms resulted in simulations where both attack rates and outbreak durations were consistent with surveillance data. The epidemiology of norovirus outbreaks in daycare and school settings cannot be well described by a simple transmission model in which all individuals start as fully susceptible. More studies on how best to design interventions which leverage population immunity and encourage more rigorous individual exclusion may improve venue-level control measures. See video abstract at http://links.lww.com/EDE/B795.

A mechanistic, stigmergy model of territory formation in solitary animals: Territorial behavior can dampen disease prevalencebut increase persistence.

Although movement ecology has leveraged models of home range formation to explore the effects of spatial heterogeneity and social cues on movement behavior, disease ecology has yet to integrate these potential drivers and mechanisms of contact behavior into a generalizable disease modeling framework. Here we ask how dynamic territory formation and maintenance might contribute to disease dynamics in a territorial, solitary predator for an indirectly transmitted pathogen. We developed a mechanistic individual-based model where stigmergy-the deposition of signals into the environment (e.g., scent marking, scraping)-dictates local movement choices and long-term territory formation, but also the risk of pathogen transmission. Based on a variable importance analysis, the length of the infectious period was the single most important variable in predicting outbreak success, maximum prevalence, and outbreak duration. Host density and rate of pathogen decay were also key predictors. We found that territoriality best reduced maximum prevalence in conditions where we would otherwise expect outbreaks to be most successful: slower recovery rates (i.e., longer infectious periods) and higher conspecific densities. However, for slower pathogen decay rates, stigmergy-driven movement increased outbreak durations relative to random movement simulations. Our findings therefore support a limited version of the "territoriality benefits" hypothesis-where reduced home range overlap leads to reduced opportunities for pathogen transmission, but with the caveat that reduction in outbreak severity may increase the likelihood of pathogen persistence. For longer infectious periods and higher host densities, key trade-offs emerged between the strength of pathogen load, the strength of the stigmergy cue, and the rate at which those two quantities decayed; this finding raises interesting questions about the evolutionary nature of these competing processes and the role of possible feedbacks between parasitism and territoriality. This work also highlights the importance of considering social cues as part of the movement landscape in order to better understand the consequences of individual behaviors on population level outcomes.

Detection and Isolation of Clostridium difficile Asymptomatic Carriers During Clostridium difficile Infection Outbreaks: An Exploratory Study.

During 4 Clostridium difficile infection outbreaks, unit-wide screening of 114 patients led to detection and isolation of 15 (13%) C. difficile asymptomatic carriers. Carriage prevalence varied between outbreaks, from 0% to 29% (P = .004). Isolating carriers was not associated with significantly shorter outbreak durations, compared with historical controls.

Effective Network Size Predicted From Simulations of Pathogen Outbreaks Through Social Networks Provides a Novel Measure of Structure-Standardized Group Size.

The transmission of infectious disease through a population is often modeled assuming that interactions occur randomly in groups, with all individuals potentially interacting with all other individuals at an equal rate. However, it is well known that pairs of individuals vary in their degree of contact. Here, we propose a measure to account for such heterogeneity: effective network size (ENS), which refers to the size of a maximally complete network (i.e., unstructured, where all individuals interact with all others equally) that corresponds to the outbreak characteristics of a given heterogeneous, structured network. We simulated susceptible-infected (SI) and susceptible-infected-recovered (SIR) models on maximally complete networks to produce idealized outbreak duration distributions for a disease on a network of a given size. We also simulated the transmission of these same diseases on random structured networks and then used the resulting outbreak duration distributions to predict the ENS for the group or population. We provide the methods to reproduce these analyses in a public R package, “enss.” Outbreak durations of simulations on randomly structured networks were more variable than those on complete networks, but tended to have similar mean durations of disease spread. We then applied our novel metric to empirical primate networks taken from the literature and compared the information represented by our ENSs to that by other established social network metrics. In AICc model comparison frameworks, group size and mean distance proved to be the metrics most consistently associated with ENS for SI simulations, while group size, centralization, and modularity were most consistently associated with ENS for SIR simulations. In all cases, ENS was shown to be associated with at least two other independent metrics, supporting its use as a novel metric. Overall, our study provides a proof of concept for simulation-based approaches toward constructing metrics of ENS, while also revealing the conditions under which this approach is most promising.

Using an agent-based model to evaluate the effect of producer specialization on the epidemiological resilience of livestock production networks.

An agent-based computer model that builds representative regional U.S. hog production networks was developed and employed to assess the potential impact of the ongoing trend towards increased producer specialization upon network-level resilience to catastrophic disease outbreaks. Empirical analyses suggest that the spatial distribution and connectivity patterns of contact networks often predict epidemic spreading dynamics. Our model heuristically generates realistic systems composed of hog producer, feed mill, and slaughter plant agents. Network edges are added during each run as agents exchange livestock and feed. The heuristics governing agents’ contact patterns account for factors including their industry roles, physical proximities, and the age of their livestock. In each run, an infection is introduced, and may spread according to probabilities associated with the various modes of contact. For each of three treatments—defined by one-phase, two-phase, and three-phase production systems—a parameter variation experiment examines the impact of the spatial density of producer agents in the system upon the length and size of disease outbreaks. Resulting data show phase transitions whereby, above some density threshold, systemic outbreaks become possible, echoing findings from percolation theory. Data analysis reveals that multi-phase production systems are vulnerable to catastrophic outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outbreak scales and durations. Key differences in network-level metrics shed light on these results, suggesting that the absence of potentially-bridging producer–producer edges may be largely responsible for the superior disease resilience of single-phase “farrow to finish” production systems.

Simulation of Cross-border Impacts Resulting from Classical Swine Fever Epidemics within the Netherlands and Germany.

The cross-border region of the Netherlands (NL) and the two German states of North Rhine Westphalia (NRW) and Lower Saxony (LS) is a large and highly integrated livestock production area. This region increasingly develops towards a single epidemiological area in which disease introduction is a shared veterinary and, consequently, economic risk. The objectives of this study were to examine classical swine fever (CSF) control strategies' veterinary and direct economic impacts for NL, NRW and LS given the current production structure and to analyse CSF's cross-border causes and impacts within the NL-NRW-LS region. The course of the epidemic was simulated by the use of InterSpread Plus, whereas economic analysis was restricted to calculating disease control costs and costs directly resulting from the control measures applied. Three veterinary control strategies were considered: a strategy based on the minimum EU requirements, a vaccination and a depopulation strategy based on NL and GER's contingency plans. Regardless of the veterinary control strategy, simulated outbreak sizes and durations for 2010 were much smaller than those simulated previously, using data from over 10 years ago. For example, worst-case outbreaks (50th percentile) in NL resulted in 30-40 infected farms and lasted for two to four and a half months; associated direct costs and direct consequential costs ranged from €24.7 to 28.6 million and €11.7 to 26.7 million, respectively. Both vaccination and depopulation strategies were efficient in controlling outbreaks, especially large outbreaks, whereas the EU minimum strategy was especially deficient in controlling worst-case outbreaks. Both vaccination and depopulation strategies resulted in low direct costs and direct consequential costs. The probability of cross-border disease spread was relatively low, and cross-border spread resulted in small, short outbreaks in neighbouring countries. Few opportunities for further cross-border harmonization and collaboration were identified, including the implementation of cross-border regions (free and diseased regions regardless of the border) in case of outbreaks within close proximity of the border, and more and quicker sharing of information across the border. It was expected, however, that collaboration to mitigate the market effects of an epidemic will create more opportunities to lower the impact of CSF outbreaks in a cross-border context.

Minimization of the Impact of Aujeszky’s Disease Outbreaks in The Netherlands: A Conceptual Framework

In the Netherlands, outbreaks of Aujeszky's Disease (AD) are controlled by vaccination and movement restriction zones (MRZ). Although this strategy avoids the socio-ethical concerns associated with pre-emptive slaughter, it can easily result in animal welfare problems and negative economic consequences. These arise because movement restrictions result in surpluses of live (vaccinated) piglets on farms. The aim is to provide insight into the development of these surpluses and its impact and to describe how measures that allow early transportation of pigs under certain conditions and to specific destinations (channelling) could reduce these problems. For the analysis, a deterministic simulation model was developed, which calculates surpluses of piglets at multiplier farms during AD outbreaks. This is performed on a weekly basis for two areas (with and without piglet surplus), three outbreak durations (minimum, moderate and long) and three strategies for movement restrictions (strict, transports within the MRZ allowed and transports outside the MRZ allowed). The results show that in case of complete movement restrictions, surpluses of piglets varying in age and vaccination status will quickly arise. These surpluses are larger for longer epidemics and can become as large as 180-340 thousand piglets (45-75% of weekly domestic production) for moderate and long epidemics, respectively. Implementation of channelling strategies that allow earlier transportation within the MRZ can reduce surpluses by about 50% to 100-150 thousand piglets maximum. Strategies that also allow transportation outside the MRZ can reduce surpluses even further to below 100 thousand piglets. It was concluded that channelling of live piglets during AD outbreaks results in a drastic reduction of problems with accommodating ready-for-transport piglets. Moreover, it reduces shortages during movement restrictions and peak supply immediately after removing the restrictions. Channelling could therefore be an important instrument to reduce the economic and animal welfare impacts of containment measures.

Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza

Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups, but there is considerable uncertainty as to the essential mechanisms and their parametrization. In this paper, we identify a number of characteristic features of influenza incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. By constraining the output of simple models to match these characteristic features, we investigate the role played by population heterogeneity, multiple strains, cross-immunity and the rate of strain evolution in the generation of incidence time series. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match observed time-series data. Our work gives estimates of the seasonal peak basic reproduction number, R0, in the range 1.6–3. Estimates of R0 are strongly correlated with the timescale for waning of immunity to current circulating seasonal influenza strain, which we estimate is between 3 and 8 years. Seasonal variation in transmissibility is largely confined to 15–30% of its mean value. While population heterogeneity and cross-immunity are required mechanisms, the degree of heterogeneity and cross-immunity is not tightly constrained. We discuss our findings in the context of other work fitting to seasonal influenza data.

Quantifying the transmissibility of human influenza and its seasonal variation in temperate regions

Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups. The long term patterns of disease are hard to capture with simple models, while the interplay of epidemiological processes with antigenic evolution makes detailed modelling difficult and computationally intensive. We identify a number of characteristic features of flu incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. We construct pseudo-likelihoods to capture these characteristic features and examine the ability of a collection of simple models to reproduce them under seasonal variation in transmission. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match time series data. The extent of matching behaviour also serves to define informative ranges for parameters governing essential dynamics. Our work gives estimates of the seasonal peak basic reproduction, R0, in the range 1.7-2.1, with the degree of seasonal variation having limited impact of these estimates. We find that it is only really possible to estimate a lower bound on the degree of seasonal variation in influenza transmissibility, namely that transmissibility in the low transmission season may be only 5-10% less than the peak value. These results give some insight into the extent to which transmissibility of the H1N1pdm pandemic virus may increase in Northern Hemisphere temperate countries in winter 2009. We find that the timescale for waning of immunity to current circulating seasonal influenza strain is between 4 and 8 years, consistent with studies of the antigenic variation of influenza, and that inter-subtype cross-immunity is restricted to low levels.

Effects of climate change on tularaemia disease activity in Sweden

Tularaemia is a vector-borne infectious disease. A large majority of cases transmitted to humans by blood-feeding arthropods occur during the summer season and is linked to increased temperatures. Therefore, the effect of climate change is likely to have an effect on tularaemia transmission patterns in highly endemic areas of Sweden. In this report, we use simulated climate change scenario data and empirical data of temperatures critical to tularaemia transmission to forecast tularaemia outbreak activity. The five high-endemic counties: Dalarna, Gävleborg, Norrbotten, Värmland and Örebro represent only 14.6% of the total population of Sweden, but have recorded 40.1–81.1% of the number of annual human tularaemia in Sweden from 1997 until 2008. We project here earlier starts and a later termination of future tularaemia outbreaks for the time period 2010–2100. For five localised outbreak areas; Gagnef (Dalarna), Ljusdal (Gävleborg), Harads (Norrbotten), Karlstad (Värmland) and Örebro municipality (Örebro), the climate scenario suggests an approximately 2°C increase in monthly average summer temperatures leading to increases in outbreak durations ranging from 3.5 weeks (Harads) to 6.6 weeks (Karlstad) between 2010 and 2100. In contrast, an analysis of precipitation scenarios indicates fairly stable projected levels of precipitation during the summer months. Thus, there should not be an increased abundance of late summer mosquitoes that are believed to be main vectors for transmission to humans in these areas. In conclusion, the results indicate that the future climate changes will lead to an increased burden of tularaemia in high-endemic areas of Sweden during the coming decades.

Variation in the VP1 Gene of Foot-And-Mouth Disease Virus Serotype a Associated with Epidemiological Characteristics of Outbreaks in the 2001 Epizootic in Argentina

A mixed binomial Bayesian regression model was used to quantify the relation between nucleotide differences in the VP1 gene of Foot-and-mouth disease virus (FMDV) serotype A, and epidemiologic characteristics of the outbreaks from which the viruses were obtained between January and December 2001 in Argentina. An increase in the probability of different nucleotides between isolates was associated with a longer time between isolation dates, a greater distance between isolation locations, an increase in the difference between attack rates, and an increase in the difference in outbreak durations. The farther apart the outbreak herds were in the southerly and easterly directions, the greater the difference in nucleotide changes. The model accurately predicted genetic distances of isolates obtained in 2001 compared with a 2002 isolate (P < 0.01), which suggested that the predictive modeling approach applied in the present study may be useful in understanding the epidemiology of evolution of FMDV and in forensic analysis of disease epidemics.

Salmonella Outbreaks in Restaurants in Minnesota, 1995 through 2003: Evaluation of the Role of Infected Foodworkers

The 23 restaurant-associated salmonellosis outbreaks that occurred in Minnesota from 1995 through 2003 were reviewed to characterize the role of infected foodworkers. The median duration of the outbreaks was 21 days (range, 1 to 517 days). The median number of culture-confirmed patron cases per outbreak was seven (range, 1 to 36 cases). The median incubation for patron cases ranged from9hto5.9 days. A specific food vehicle was implicated in four outbreaks and suspected in five. Salmonella of the same serotype and pulsed-field gel electrophoresis subtype as that found in patrons was recovered from foodworkers in 19 outbreaks. Overall, 12% (129 of 1,033) of foodworkers tested positive for Salmonella. Sixty-four (53%) of 121 Salmonella-positive foodworkers reported not having had a recent gastrointestinal illness. Overall, the median duration of Salmonella shedding was 16 days. Among foodworkers who reported gastrointestinal illness, the median shedding duration was 30 days as compared with 3 days for asymptomatic foodworkers. Positive environmental samples were recovered in 4 (33%) of 12 outbreaks. No specific food vehicle was identified in any outbreaks associated with Salmonella-positive environmental samples. The median duration of outbreaks with positive environmental samples (187 days) was significantly longer than the median duration of outbreaks with negative environmental results (26 days, P = 0.03). A higher proportion of Salmonella-positive foodworkers (22 versus 8%) was identified in outbreaks with positive environmental samples. Salmonella outbreaks in restaurants are frequently prolonged yet produce a small number of confirmed patron cases. Prolonged outbreak durations suggest a persistent reservoir of contamination. Infected foodworkers likely serve as an important source for Salmonella transmission. Therefore, assessment of foodworker infection is essential for controlling restaurant outbreaks.