Coronavirus disease 2019 (COVID-19) has been described as having an overdispersed offspring distribution, i.e. high variation in the number of secondary transmissions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) per single primary COVID-19 case. Accordingly, countermeasures focused on high-risk settings and contact tracing could efficiently reduce secondary transmissions. However, as variants of concern with elevated transmissibility continue to emerge, controlling COVID-19 with such focused approaches has become difficult. It is vital to quantify temporal variations in the offspring distribution dispersibility. Here, we investigated offspring distributions for periods when the ancestral variant was still dominant (summer, 2020; wave 2) and when Alpha variant (B.1.1.7) was prevailing (spring, 2021; wave 4). The dispersion parameter (k) was estimated by analysing contact tracing data and fitting a negative binomial distribution to empirically observed offspring distributions from Nagano, Japan. The offspring distribution was less dispersed in wave 4 (k = 0.32; 95% confidence interval (CI) 0.24–0.43) than in wave 2 (k = 0.21 (95% CI 0.13–0.36)). A high proportion of household transmission was observed in wave 4, although the proportion of secondary transmissions generating more than five secondary cases did not vary over time. With this decreased variation, the effectiveness of risk group-focused interventions may be diminished.

Disease transmission and behaviour change are both fundamentally social phenomena. Behaviour change can have profound consequences for disease transmission, and epidemic conditions can favour the more rapid adoption of behavioural innovations. We analyse a simple model of coupled behaviour change and infection in a structured population characterised by homophily and outgroup aversion. Outgroup aversion slows the rate of adoption and can lead to lower rates of adoption in the later-adopting group or even behavioural divergence between groups when outgroup aversion exceeds positive ingroup influence. When disease dynamics are coupled to the behaviour-adoption model, a wide variety of outcomes are possible. Homophily can either increase or decrease the final size of the epidemic depending on its relative strength in the two groups and on R0 for the infection. For example, if the first group is homophilous and the second is not, the second group will have a larger epidemic. Homophily and outgroup aversion can also produce dynamics suggestive of a ‘second wave’ in the first group that follows the peak of the epidemic in the second group. Our simple model reveals dynamics that are suggestive of the processes currently observed under pandemic conditions in culturally and/or politically polarised populations such as the USA.

The outbreak of coronavirus disease-2019 (COVID-19) impacts public health dramatically around the world. The demographic characteristics, exposure history, dates of illness onset and dates of confirmed diagnosis were collected from the data of 24 family clusters from Beijing. The characteristics of the cases and the estimated key epidemiologic time-to-event distributions were described. The basic reproductive number (R0) was calculated. Among 89 confirmed COVID-19 patients from 24 family clusters, the median age was 38.0 years and 43.8% were male. The median of incubation period was 5.08 days (95% confidence interval (CI) 4.17–6.21). The median of serial interval was 6.00 days (95% CI 5.00–7.00). The basic reproductive number (R0) was 2.06 (95% CI 2.02–2.08). The median of onset-to-care-seeking days and the median of onset-to-hospital admission days were significantly reduced after 23 January 2020, which implied the enhanced public health awareness among families. With epidemic containment measures in place, the results can inform health authorities about possible extent of epidemic transmission within families. Furthermore, following initiation of interventions, public health measures are not only important for curbing the epidemic spread at the community level but also improve health seeking behaviour at the individual level.

As Bulgaria transitions away from Global Fund grant, robust estimates of the comparative impact of the various response strategies under consideration are needed to ensure sustained effectiveness of the tuberculosis (TB) programme. We tailored an established mathematical model for TB control to the epidemic in Bulgaria to project the likely outcomes of seven intervention scenarios. Under existing programmatic conditions projected forward, the country's targets for achieving TB elimination in the coming decades will not be achieved. No interventions under consideration were predicted to accelerate the baseline projected reduction in epidemiological indicators significantly. Discontinuation of the ‘Open Doors’ program and activities of non-governmental organisations would result in a marked exacerbation of the epidemic (increasing incidence in 2035 by 6–8% relative to baseline conditions projected forward). Changing to a short course regimen for multidrug-resistant TB (MDR-TB) would substantially decrease MDR-TB mortality (by 21.6% in 2035 relative to baseline conditions projected forward). Changing to ambulatory care for eligible patients would not affect TB burden but would be markedly cost-saving. In conclusion, Bulgaria faces important challenges in transitioning to a primarily domestically-financed TB programme. The country should consider maintaining currently effective programs and shifting towards ambulatory care to ensure program sustainability.

To control hepatitis A spread by vaccination, accurate estimation of transmissibility is vital. Regan et al. (2016) proposed a model of hepatitis A virus (HAV) transmission and used least squares to calibrate model to the 1991/1992 HAV outbreak in men who have sex with men (MSM) in Sydney, Australia. Based on the estimate of R0, they obtained the critical immunity of 70% and showed that when the proportion immune <70%, there is a definite chance for outbreaks to take place. The immunity level from previous surveys ranges from 32% to 64% after 1996 while no outbreaks in Australian MSMs have been reported since 1996. Further noticing the ill-distributed parameters, we argue that their estimate of R0 is not accurate. In this study, we revisited their model by Bayesian inference, which has privilege over least squares. We obtained the appropriate posterior distributions of parameters and the estimate of R0 ranges from 1.38 to 2.89, indicating a critical immunity of 65%. The reduction in critical immunity and outbreak probabilities predicts the absence of outbreaks in Australian MSMs since 1996. Our study shows the importance of using appropriate methods to provide reliable and accurate estimates of the model parameters especially the transmissibility.

While group formation provides antipredatory defences, increases foraging efficiency and mating opportunities, it can be counterintuitive by promoting disease transmission amongst social hosts. Upon introduction of a pathogen, uninfected individuals often modify their social preferences to reduce infection risk. Infected hosts also exhibit behavioural changes, for example, removing themselves from a group to prevent an epidemic. Conversely, here we show how Trinidadian guppies infected with a directly transmitted ectoparasite, Gyrodactylus turnbulli, significantly increase their contact rates with uninfected conspecifics. As uninfected fish never perform this behaviour, this is suggestive of a parasite-mediated behavioural response of infected hosts, presumably to offload their parasites. In the early stages of infection, however, such behavioural modifications are ineffective in alleviating parasite burdens. Additionally, we show that fish exposed to G. turnbulli infections for a second time, spent less time associating than those exposed to parasites for the first time. We speculate that individuals build and retain an infection cue repertoire, enabling them to rapidly recognize and avoid infectious conspecifics. This study highlights the importance of considering host behavioural modifications when investigating disease transmission dynamics.

Field surveys indicate that host population size, rather than density, is the most important determinant of monogenean infection dynamics. To verify this prediction, epidemic parameters were monitored for 70 days at five host population sizes held at constant density using a goldfish – Gyrodactylus kobayashii laboratory model. During the first 20 days, the rate of increase of prevalence and mean abundance was faster in small host populations. Total mean prevalence and total mean abundance throughout the experiment were not significantly affected by host population sizes. Higher transmission rates were detected in larger host populations. However, there were no significant differences in effective contact rates among the five host populations on each sampling day during the first 20 days, implying that contact rates may be saturated at a sufficiently high host density. These results demonstrate that the epidemic occurs more quickly in smaller host populations at the beginning of the experiment. However, the epidemic is independent of the host population size due to the similar effective contact rates in the five population sizes. Significant negative influence of the initial body condition (Kn) of uninfected goldfish on total mean abundance of parasites suggests that susceptibility of hosts is also a determinant of parasite transmission.

An outbreak of influenza A(H1N1)pdm09 was detected during the ongoing community-based surveillance of influenza-like illness (ILI). Among reported 119 influenza A(H1N1)pdm09 cases (59 cases in the year 2012 and 60 cases in 2015) in summer months, common clinical features were fever (100%), cough (90·7%), sore throat (85·7%), nasal discharge (48·7%), headache (55·5%), fatigue (18·5%), breathlessness (3·4%), and ear discharge (1·7%). Rise in ILI cases were negatively correlated with the seasonal factors such as relative humidity (Karl Pearson's correlation coefficient, i.e. r = −0·71 in the year 2012 and r = −0·44 in the year 2015), while rise in ILI cases were positively correlated with the temperature difference (r = 0·44 in the year 2012 and r = 0·77 in the year 2015). The effective reproduction number R, was estimated to be 1·30 in 2012 and 1·64 in 2015. The study highlights the rise in unusual influenza activity in summer month with high attack rate of ILI among children aged ⩽9 years. Children in this age group may need special attention for influenza vaccination. Influenza A(H1N1)pdm09 outbreak was confirmed in inter-seasonal months during the surveillance of ILI in Pune, India, 2012–2015.

RSV is the most important viral cause of pneumonia and bronchiolitis in children worldwide and has been associated with significant disease burden. With the renewed interest in RSV vaccines, we provide realistic estimates on duration, and influencing factors on RSV shedding which are required to better understand the impact of vaccination on the virus transmission dynamics. The data arise from a prospective study of 47 households (493 individuals) in rural Kenya, followed through a 6-month period of an RSV seasonal outbreak. Deep nasopharyngeal swabs were collected twice each week from all household members, irrespective of symptoms, and tested for RSV by multiplex PCR. The RSV G gene was sequenced. A total of 205 RSV infection episodes were detected in 179 individuals from 40 different households. The infection data were interval censored and assuming a random event time between observations, the average duration of virus shedding was 11·2 (95% confidence interval 10·1–12·3) days. The shedding durations were longer than previous estimates (3·9–7·4 days) based on immunofluorescence antigen detection or viral culture, and were shown to be strongly associated with age, severity of infection, and revealed potential interaction with other respiratory viruses. These findings are key to our understanding of the spread of this important virus and are relevant in the design of control programmes.

Transmission dynamics of the actinospore stage of Ceratomyxa shasta to the salmonid host were investigated under field and laboratory conditions. The number of parasites transmitted and the transmission rate were compared between 2 different exposure durations and also among different water velocities, by means of field exposures. Under laboratory conditions, the number of parasites transmitted and the transmission rates were compared across a broader range of water velocities and also at different water temperatures. Transmission rate was not constant over time as the number of parasites transmitted increased non-linearly between the 2 exposure durations. Transmission was also inversely related to water velocity and there was a threshold to transmission between 0·2–0·3 m s−1. Lastly, transmission rate increased with water temperature up to 18 °C then decreased at 23 °C. These experiments provide a range of values of transmission that will be incorporated into an epidemiological model to simulate the effectiveness of different management strategies. Additionally, these experiments provided novel information on the effects of environmental conditions (i.e. water velocity and water temperature) on the transmission dynamics between the salmonid host and the actinospore stage.

Increased frequency and severity of stressors associated with climate change are drastically altering ecosystems. Caribbean coral reefs differ markedly from just 30 years ago, with much restructuring attributable to infectious disease outbreaks. Using a classic epidemiological approach, we demonstrate how density-dependent demographic rates serve as a mechanism for intrinsic coral resilience to population perturbations arising from disturbances such as disease. We explore the impact of allowing infection status to influence demographic rates and ascertain outbreak thresholds that are corroborated by epizootic patterns observed in the field. We discuss how our threshold calculations may provide metrics of coral epizootic early warning systems. Integrating our infection model with equations describing the interspecific competition for space between coral and macroalgae, we provide new mechanistic understanding of the influence that coral life history dynamism and infectious disease have on the changing face of these threatened ecosystems.

Landscape epidemiology and landscape genetics combine advances in molecular techniques, spatial analyses and epidemiological models to generate a more real-world understanding of infectious disease dynamics and provide powerful new tools for the study of RNA viruses. Using dog rabies as a model we have identified how key questions regarding viral spread and persistence can be addressed using a combination of these techniques. In contrast to wildlife rabies, investigations into the landscape epidemiology of domestic dog rabies requires more detailed assessment of the role of humans in disease spread, including the incorporation of anthropogenic landscape features, human movements and socio-cultural factors into spatial models. In particular, identifying and quantifying the influence of anthropogenic features on pathogen spread and measuring the permeability of dispersal barriers are important considerations for planning control strategies, and may differ according to cultural, social and geographical variation across countries or continents. Challenges for dog rabies research include the development of metapopulation models and transmission networks using genetic information to uncover potential source/sink dynamics and identify the main routes of viral dissemination. Information generated from a landscape genetics approach will facilitate spatially strategic control programmes that accommodate for heterogeneities in the landscape and therefore utilise resources in the most cost-effective way. This can include the efficient placement of vaccine barriers, surveillance points and adaptive management for large-scale control programmes.

A mathematical model that describes the transmission dynamics of Theileria annulata is proposed that consists of 2 host components: the Hyalomma tick population and a compartmental model of T. annulata infection in the cattle population. The model was parameterized using data describing tick infestation and the infection status of cattle in Turkey from 2006 to 2008. The tick attachment rates are highly seasonal and because of the temporal separation of infectious and susceptible ticks virtually all ticks are infected by carrier cattle, so that annual peaks of disease in cattle do not impact on infection in the Hyalomma tick population. The impact of intervention measures that target the tick population both on the host and in the environment and their impact on the transmission of T. annulata were investigated. Interventions that have a limited ‘one-off’ impact and interventions that have a more permanent impact were both considered. The results from the model show the importance of targeting ticks during the period when they have left their first host as nymphs but have yet to feed on their second host.

The kernel of modelling transmission dynamics of infectious diseases lies in constructing the force of infection (FOI). Traditionally, it was based on mass-action law. In this paper, we show, based on survey data of Escherichia coli O157 infection on Scottish cattle farms, that the actual form of FOI deviates greatly from mass-action law. Further, control effectiveness deviates qualitatively: the epidemic of mass-action FOI can be controlled with a control effort larger than the so-called herd immunity, while the epidemic inferred from the survey data of E. coli O157 infection was shown to be difficult to control. This indicates that, at least for E. coli O157 infection on cattle farms, it is risky to rely on models of transmission dynamics that were based on mass-action law to design the optimal intervention programme for infectious diseases. This suggests the importance of collecting epidemic data and model selection from data-driven models to infer the most likely model of transmission dynamics.

The pattern of transmission of human schistosomiasis was studied in Amagunze Village, eastern Nigeria, during 1986–1987. The prevalence of Schistosoma haematobium in 119 schoolboys aged 5–12 years was 79%. The geometric mean of intensity of infection was 49 eggs/10 ml urine and the frequency of visible haematuria was 25·2%. No S. mansoni infections were demonstrated. A marked seasonality in population density of Bulinus truncatus, B. forskalii and Biomphalaria pfeifferi was demonstrated with reduced densities during the late rainy and early dry seasons. Schistosoma sp. infected B. truncatus were found in the late dry and early rainy seasons in 2 out of 7 major human water contact sites studied. Seasonality and focality of transmission of S. haematobium and its high endemicity in the area were thus demonstrated.

Two mathematical models are developed that investigate the transmission dynamics of Theileria parva by the ixodid tickRhipicephalus appendiculatus to cattle in endemically stable areas. A method of estimating the rate of infection to cattle ofT. parva at the endemically stable state is given. Empirical estimates of ail the parameters in the model are available. The degree to which animals that have recovered from theileriosis (the ‘carrier’ state) are able to transmit the infection to tick nymphs or larvae is a crucial determinant of the dynamics of infection in a herd. Two control methods influencing the transmission of infection are considered – infection and treatment immunization and the reduction in tick feeding by acaricide application. The impact of each method on the transmission of infection is evaluated. Future developments and the data required to predict the dynamics of T. parva infections in cattle and ticks are discussed.

LYMFASIM is a simulation model for lymphatic filariasis transmission and control. We quantified its parameters to simulate Wuchereria bancrofti transmission by Anopheles mosquitoes in African villages, using a wide variety of reported data. The developed model captures the general epidemiological patterns, but also the differences between communities. It was calibrated to represent the relationship between mosquito biting rate and the prevalence of microfilariae (mf) in the human population, the age-pattern in mf prevalence, and the relation between mf prevalence and geometric mean mf intensity. Explorative simulations suggest that the impact of mass treatment depends strongly on the mosquito biting rate and on the assumed coverage, compliance and efficacy. Our sensitivity analysis showed that some biological parameters strongly influence the predicted equilibrium pre-treatment mf prevalence (e.g. the lifespan of adult worms and mf). Other parameters primarily affect the post-treatment trends (e.g. severity of density dependence in the mosquito uptake of infection from the human blood, between-person variability in exposure to mosquito bites). The longitudinal data, which are being collected for evaluation of ongoing elimination programmes, can help to further validate the model. The model can help to assess when ongoing elimination activities in African populations can be stopped and to design surveillance schemes. It can be a valuable tool for decision making in the Global Programme to Eliminate Lymphatic Filariasis.

Perkinsus marinus is a severe pathogen of the oyster Crassostrea virginica on the East Coast of the United States. Transmission dynamics of this parasite were investigated in situ for 2 consecutive years (May through October) at 2 lower Chesapeake Bay sites. Compared to previous studies where seasonal infection patterns in oysters were measured, this study also provided parasite water column abundance data measured using real-time PCR. As previously observed, salinity and temperature modulated parasite transmission dynamics. Using regression analysis, parasite prevalence, oyster mortalities and parasite water column abundance were significantly positively related to salinity. Perkinsus marinus weighted prevalence in wild oysters and parasite water column abundance both were significantly related to temperature, but the responses lagged 1 month behind temperature. Parasite water column abundance was the highest during August (up to 1200 cells/l) and was significantly related to P. marinus weighted prevalence in wild oysters, and to wild oyster mortality suggesting that parasites are released in the environment via both moribund and live hosts (i.e. through feces). Incidence was not significantly related to parasite water column abundance, which seems to indicate the absence of a linear relationship or that infection acquisition is controlled by a more complex set of parameters.