A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks

A better characterization of the early growth dynamics of an epidemic is needed to dissect the important drivers of disease transmission. We introduce a 2-parameter generalized-growth model to characterize the ascending phase of an outbreak and capture epidemic profiles ranging from sub-exponential to exponential growth. We test the model against empirical outbreak data representing a variety of viral pathogens and provide simulations highlighting the importance of sub-exponential growth for forecasting purposes. We applied the generalized-growth model to 20 infectious disease outbreaks representing a range of transmission routes. We uncovered epidemic profiles ranging from very slow growth (p=0.14 for the Ebola outbreak in Bomi, Liberia (2014)) to near exponential (p>0.9 for the smallpox outbreak in Khulna (1972), and the 1918 pandemic influenza in San Francisco). The foot-and-mouth disease outbreak in Uruguay displayed a profile of slower growth while the growth pattern of the HIV/AIDS epidemic in Japan was approximately linear. The West African Ebola epidemic provided a unique opportunity to explore how growth profiles vary by geography; analysis of the largest district-level outbreaks revealed substantial growth variations (mean p=0.59, range: 0.14-0.97). Our findings reveal significant variation in epidemic growth patterns across different infectious disease outbreaks and highlights that sub-exponential growth is a common phenomenon. Sub-exponential growth profiles may result from heterogeneity in contact structures or risk groups, reactive behavior changes, or the early onset of interventions strategies, and consideration of "deceleration parameters" may be useful to refine existing mathematical transmission models and improve disease forecasts.Comment: 31 pages, 9 Figures, 1 Supp. Figure, 1 Table, final accepted version (in press), Epidemics - The Journal on Infectious Disease Dynamics, 201

Quantifying the transmission potential of pandemic influenza

This article reviews quantitative methods to estimate the basic reproduction number of pandemic influenza, a key threshold quantity to help determine the intensity of interventions required to control the disease. Although it is difficult to assess the transmission potential of a probable future pandemic, historical epidemiologic data is readily available from previous pandemics, and as a reference quantity for future pandemic planning, mathematical and statistical analyses of historical data are crucial. In particular, because many historical records tend to document only the temporal distribution of cases or deaths (i.e. epidemic curve), our review focuses on methods to maximize the utility of time-evolution data and to clarify the detailed mechanisms of the spread of influenza. First, we highlight structured epidemic models and their parameter estimation method which can quantify the detailed disease dynamics including those we cannot observe directly. Duration-structured epidemic systems are subsequently presented, offering firm understanding of the definition of the basic and effective reproduction numbers. When the initial growth phase of an epidemic is investigated, the distribution of the generation time is key statistical information to appropriately estimate the transmission potential using the intrinsic growth rate. Applications of stochastic processes are also highlighted to estimate the transmission potential using the similar data. Critically important characteristics of influenza data are subsequently summarized, followed by our conclusions to suggest potential future methodological improvements.Comment: 79 pages (revised version), 3 figures; added 1 table and minor revisions were made in the main text; to appear in Physics of Life Reviews; Gerardo's website (http://www.public.asu.edu/~gchowel/), Hiroshi's website (http://plaza.umin.ac.jp/~infepi/hnishiura.htm

Characterizing the Transmission Dynamics and Control of Ebola Virus Disease

Carefully calibrated transmission models have the potential to guide public health officials on the nature and scale of the interventions required to control epidemics. In the context of the ongoing Ebola virus disease (EVD) epidemic in Liberia, Drake and colleagues, in this issue of PLOS Biology, employed an elegant modeling approach to capture the distributions of the number of secondary cases that arise in the community and health care settings in the context of changing population behaviors and increasing hospital capacity. Their findings underscore the role of increasing the rate of safe burials and the fractions of infectious individuals who seek hospitalization together with hospital capacity to achieve epidemic control. However, further modeling efforts of EVD transmission and control in West Africa should utilize the spatial-temporal patterns of spread in the region by incorporating spatial heterogeneity in the transmission process. Detailed datasets are urgently needed to characterize temporal changes in population behaviors, contact networks at different spatial scales, population mobility patterns, adherence to infection control measures in hospital settings, and hospitalization and reporting rates

Household and Community Transmission of the Asian Influenza A (H2n2) and Influenza B Viruses In 1957 and 1961

This study analyzed the distribution of the number of cases in households of various sizes, reconsidering previous survey data from the Asian influenza A (H2N2) pandemic in 1957 and the influenza B epidemic in 1961. The final size distributions for the number of household cases were extracted from four different data sources (n = 547, 671, 92 and 263 households), and a probability model was applied to estimate the community probability of infection (CPI) and household secondary attack rate (SAR). For the 1957 Asian influenza pandemic, the CPI and household SAR were estimated to be 0.42 [95% confidence intervals (CI): 0.37, 0.47] and 7.06% (95% CI: 4.73, 9.44), respectively, using data from Tokyo. The figures for the same pandemic using data from Osaka were 0.21 (95% CI: 0.19, 0.22) and 9.07% (95% CI: 6.73, 11.53), respectively. Similarly, the CPI and household SAR for two different datasets of influenza B epidemics in Osaka in 1961 were estimated as 0.37 (95% CI: 0.30, 0.44) and 18.41% (95% CI: 11.37, 25.95) and 0.20 (95% CI: 0.13, 0.28) and 10.51% (95% CI: 8.01, 13.15), respectively. Community transmission was more frequent than household transmission, both for the Asian influenza pandemic and the influenza B epidemic, implying that community-based countermeasures (eg, area quarantine and social distancing) may play key roles in influenza interventions

Estimation of Dog-bite rates and evaluation of Healthcare Seeking Behaviors following dog bite, Haiti

Abstract Background: Haiti has been identified as one of only several countries in the Western Hemisphere in which canine rabies control efforts have succeeded in eliminating dog-mediated human rabies deaths. In 2016, a study was conducted to test several alternative vaccination methods that may compliment the current central point vaccination program. During this study, households within the Croix de Bouquet community completed a questionnaire regarding the dog ownership, roaming status, vaccination coverage of the dog and bite victims and their healthcare seeking behaviors within the household. The aim of this analysis was to determine the incidence of humans being bitten by dogs, and the victims’ healthcare seeking behaviors for medical care and post-exposure prophylaxis (PEP) regimen.With the goal of identifying barriers and developing programs to improve timely PEP delivery to persons with likely rabies exposures. Methods: During the door-to-door (DD) vaccination campaign in August 2016, the surveyors completed a household questionnaire by interviewing respondents in the Croix de Bouquet community, West Department of Haiti. The questionnaires highlighted questions regarding bite events within the household. Information recorded on the event was the victim age, month of bite, animal ownership, bite location, case definition of a potential rabid case, whether the victim sought medical care after the bite event, and the choice to receive PEP and complete PEP. We were able to determine the incidence rate of humans bitten by dogs in this community. When applicable, 2-tailed Chi-square test or Fisher’s exact test were calculated to determine the relationship between variables. We also used Multiple Logistic Modeling to analyze the variance through likelihood ratio and Wald tests of fixed effects in generalized linear models to identify associations between dog ownership, dog vaccination, and human healthcare seeking behaviors. Results:Among the total respondent population, there was 111 bite victims within the total household population reported (n = 6993). The annual bite incidence was 3.7% (95% CI 3.2% – 4.2%). A little over half of the victims (52.3%) sought healthcare for the bite wound. However, only 11.7% completed at least three doses of the rabies post-exposure prophylaxis series. Responsible dog owners for poor versus good was: (OR = 3.337) for adequate versus good was: (OR = 1.749) (p= .0032). Households with dogs that died of a rabies-like illness 1 death versus 0 deaths (OR = 2.43), 2 vs 0 deaths (OR = 5.441), and 3 vs 0 (OR = 16.662) (p For healthcare seeking behaviors the following variables were modeled: risk surrounding the event, if the victim sought medical care, the number of people living in the household, rabies-like illness related deaths in the household within the past year, time from the hospital, victim’s age, if the household experienced more than 1 bite, and the economic status of the household. After backwards selection within the multivariate model for healthcare seeking behaviors, risk category was the only risk factor. The risk score comprised of the ownership of the animal that bit, anatomical location of the bite, and the case definition of a rabid dog, was a factor associated with PEP completion of the bite victim. Low risk versus high risk (OR = 8.750) and medium risk versus high risk (OR = 1.923). Conclusions: Responsible dog ownership relates to lower incidence of canine bites within the Haiti community, Croix De Bouquet. A positive association between responsible dog ownership and completion of PEP series was noted, potentially indicating that awareness of dog-health issues improves dog owner’s understanding of the importance of rabies PEP. Respondents demonstrating a relatively high response rate to seeking healthcare, may be attributed the current HARSP program and Ministère de l\u27Agriculture, des Ressources Naturelles et du Développement Rural (MARNDR), in collaboration with the Ministère de la Santé Publique et de la Population (MSPP), Christian Veterinary Mission (CVM) and the United States Centers for Disease Control and Prevention (CDC) that was established in 2011. [2] Time required to reach a hospital was a barrier to seeking healthcare, health officials should consider establishing more community-bite centers to improve bite-victim healthcare seeking. Financial obligations were also implicated as a barrier to not seeking medical care as well as not completing the post-exposure prophylaxis dosage. Healthcare providers should consider providing the vaccination campaign on a routine bases to reach the population that are not able to pay for medical services

Rurality and pandemic influenza: geographic heterogeneity in the risks of infection and death in Kanagawa, Japan (1918–1919)

Aim To characterise the impact of rurality on the spread of pandemic influenza by exploring both the numbers of cases and deaths in Kanagawa Prefecture, Japan, from October 1918 to April 1919 inclusive. Method In addition to the numbers of influenza cases and deaths, population sizes were extracted from census data, permitting estimations of morbidity, mortality, and case fatality by 199 different regions (population 1.4 million). These outcomes were compared between four groups; cities (n=6), larger towns (38), smaller towns (101), and villages (54). Results Whereas crude mortality in villages was lower than those of other population groups, the morbidity appeared to be the highest in villages, revealing significant difference compared to all cities and towns [risk ratio=0.601 (95% confidence interval: 0.600–0.602)]. Villages also yielded the lowest case fatality, the difference of which was statistically significant among four population groups (p=0.02). Conclusion Rurality did not show a predictive value of protection against pandemic influenza in Kanagawa. Lower morbidity in the towns and cities is likely explained by effective preventive measures in urban areas. High morbidity in rural areas highlights the potential importance of social distancing measures in order to minimise infections in the event of the next influenza pandemic