Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings.

Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014-16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD's incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.

Reconstruction and prediction of viral disease epidemics.

A growing number of infectious pathogens are spreading among geographic regions. Some pathogens that were previously not considered to pose a general threat to human health have emerged at regional and global scales, such as Zika and Ebola Virus Disease. Other pathogens, such as yellow fever virus, were previously thought to be under control but have recently re-emerged, causing new challenges to public health organisations. A wide array of new modelling techniques, aided by increased computing capabilities, novel diagnostic tools, and the increased speed and availability of genomic sequencing allow researchers to identify new pathogens more rapidly, assess the likelihood of geographic spread, and quantify the speed of human-to-human transmission. Despite some initial successes in predicting the spread of acute viral infections, the practicalities and sustainability of such approaches will need to be evaluated in the context of public health responses.

Quantifying potentially infectious sharing patterns among people who inject drugs in Baltimore, USA.

Mixing matrices quantify how people with similar or different characteristics make contact with each other, creating potential for disease transmission. Little empirical data on mixing patterns among persons who inject drugs (PWID) are available to inform models of blood-borne disease such as HIV and hepatitis C virus. Egocentric drug network data provided by PWID in Baltimore, Maryland between 2005 and 2007 were used to characterise drug equipment-sharing patterns according to age, race and gender. Black PWID and PWID who were single (i.e. no stable sexual partner) self-reported larger equipment-sharing networks than their white and non-single counterparts. We also found evidence of assortative mixing according to age, gender and race, though to a slightly lesser degree in the case of gender. Highly assortative mixing according to race and gender highlights the existence of demographically isolated clusters, for whom generalised treatment interventions may have limited benefits unless targeted directly. These findings provide novel insights into mixing patterns of PWID for which little empirical data are available. The age-specific assortativity we observed is also significant in light of its role as a key driver of transmission for other pathogens such as influenza and tuberculosis.

Travel distance and human movement predict paths of emergence and spatial spread of chikungunya in Thailand.

Human movement contributes to the probability that pathogens will be introduced to new geographic locations. Here we investigate the impact of human movement on the spatial spread of Chikungunya virus (CHIKV) in Southern Thailand during a recent re-emergence. We hypothesised that human movement, population density, the presence of habitat conducive to vectors, rainfall and temperature affect the transmission of CHIKV and the spatiotemporal pattern of cases seen during the emergence. We fit metapopulation transmission models to CHIKV incidence data. The dates at which incidence in each of 151 districts in Southern Thailand exceeded specified thresholds were the target of model fits. We confronted multiple alternative models to determine which factors were most influential in the spatial spread. We considered multiple measures of spatial distance between districts and adjacency networks and also looked for evidence of long-distance translocation (LDT) events. The best fit model included driving-distance between districts, human movement, rubber plantation area and three LDT events. This work has important implications for predicting the spatial spread and targeting resources for control in future CHIKV emergences. Our modelling framework could also be adapted to other disease systems where population mobility may drive the spatial advance of outbreaks.

Understanding dengue virus evolution to support epidemic surveillance and counter-measure development.

Dengue virus (DENV) causes a profound burden of morbidity and mortality, and its global burden is rising due to the co-circulation of four divergent DENV serotypes in the ecological context of globalization, travel, climate change, urbanization, and expansion of the geographic range of the Ae.aegypti and Ae.albopictus vectors. Understanding DENV evolution offers valuable opportunities to enhance surveillance and response to DENV epidemics via advances in RNA virus sequencing, bioinformatics, phylogenetic and other computational biology methods. Here we provide a scoping overview of the evolution and molecular epidemiology of DENV and the range of ways that evolutionary analyses can be applied as a public health tool against this arboviral pathogen.

Using age-stratified incidence data to examine the transmission consequences of pertussis vaccination.

Pertussis is a highly infectious respiratory disease that has been on the rise in many countries worldwide over the past several years. The drivers of this increase in pertussis incidence remain hotly debated, with a central and long-standing hypothesis that questions the ability of vaccines to eliminate pertussis transmission rather than simply modulate the severity of disease. In this paper, we present age-structured case notification data from all provinces of Thailand between 1981 and 2014, a period during which vaccine uptake rose substantially, permitting an evaluation of the transmission impacts of vaccination. Our analyses demonstrate decreases in incidence across all ages with increased vaccine uptake - an observation that is at odds with pertussis case notification data in a number of other countries. To explore whether these observations are consistent with a rise in herd immunity and a reduction in bacterial transmission, we analyze an age-structured model that incorporates contrasting hypotheses concerning the immunological and transmission consequences of vaccines. Our results lead us to conclude that the most parsimonious explanation for the combined reduction in incidence and the shift to older age groups in the Thailand data is vaccine-induced herd immunity.

Big city, small world: density, contact rates, and transmission of dengue across Pakistan.

Macroscopic descriptions of populations commonly assume that encounters between individuals are well mixed; i.e. each individual has an equal chance of coming into contact with any other individual. Relaxing this assumption can be challenging though, due to the difficulty of acquiring detailed knowledge about the non-random nature of encounters. Here, we fitted a mathematical model of dengue virus transmission to spatial time-series data from Pakistan and compared maximum-likelihood estimates of 'mixing parameters' when disaggregating data across an urban-rural gradient. We show that dynamics across this gradient are subject not only to differing transmission intensities but also to differing strengths of nonlinearity due to differences in mixing. Accounting for differences in mobility by incorporating two fine-scale, density-dependent covariate layers eliminates differences in mixing but results in a doubling of the estimated transmission potential of the large urban district of Lahore. We furthermore show that neglecting spatial variation in mixing can lead to substantial underestimates of the level of effort needed to control a pathogen with vaccines or other interventions. We complement this analysis with estimates of the relationships between dengue transmission intensity and other putative environmental drivers thereof.

Close encounters of the infectious kind: methods to measure social mixing behaviour.

A central tenet of close-contact or respiratory infection epidemiology is that infection patterns within human populations are related to underlying patterns of social interaction. Until recently, few researchers had attempted to quantify potentially infectious encounters made between people. Now, however, several studies have quantified social mixing behaviour, using a variety of methods. Here, we review the methodologies employed, suggest other appropriate methods and technologies, and outline future research challenges for this rapidly advancing field of research.

The population ecology of infectious diseases: pertussis in Thailand as a case study.

Many of the fundamental concepts in studying infectious diseases are rooted in population ecology. We describe the importance of population ecology in exploring central issues in infectious disease research including identifying the drivers and dynamics of host-pathogen interactions and pathogen persistence, and evaluating the success of public health policies. The use of ecological concepts in infectious disease research is demonstrated with simple theoretical examples in addition to an analysis of case notification data of pertussis, a childhood respiratory disease, in Thailand as a case study. We stress that further integration of these fields will have significant impacts in infectious diseases research.

A long-lasting measles epidemic in Maroua, Cameroon 2008-2009: mass vaccination as response to the epidemic.

BACKGROUND: A measles outbreak occurred in Maroua, Cameroon, from January 2008 to April 2009. In accordance with recent World Health Organization guidelines, an outbreak-response immunization (ORI) was conducted in January 2009. The aim of this study was to investigate the causes of the epidemic in order to guide vaccination strategies. METHODS: We performed a stratified household-based survey using cluster sampling to determine measles vaccination coverage in children aged 9 months to 15 years. We defined 3 strata based on measles incidence. Next, we performed a case-control study to measure vaccine effectiveness (VE). Cases were obtained from health center registries. Controls were selected among respondents to the coverage survey. RESULTS: The vaccination-coverage survey included 2963 children in total. The overall routine vaccination coverage was 74.1% (95% confidence interval [CI]: 70.0%-78.3%). Measles incidence was inversely proportional to routine vaccination coverage, with high incidence associated with coverage of 71% and low incidence associated with coverage of 84%. The overall VE was 94% (95% CI, 86.7%-97.4%). After the ORI in January 2009, the coverage was >90% in all strata and measles incidence declined rapidly. DISCUSSION: Our results confirm that insufficient vaccination coverage was the main reason for this epidemic. The ORI conducted in January 2009 contributed both to control the epidemic and to increase the vaccination coverage to desirable levels.

Maintaining high rates of measles immunization in Africa.

Supplementary immunization activities (SIAs) are important in achieving high levels of population immunity to measles virus. Using data from a 2006 survey of measles vaccination in Lusaka, Zambia, we developed a model to predict measles immunity following routine vaccination and SIAs, and absent natural infection. Projected population immunity was compared between the current programme and alternatives, including supplementing routine vaccination with a second dose, or SIAs at 1-, 2-, 3-, 4- and 5-year intervals. Current routine vaccination plus frequent SIAs could maintain high levels of population immunity in children aged <5 years, even if each frequent SIA has low coverage (e.g. ≥ 72% for bi-annual 60% coverage SIAs vs. ≥ 69% for quadrennial 95% coverage SIAs). A second dose at 12 months with current coverage could achieve 81% immunity. Circulating measles virus will only increase population immunity. Public health officials should consider frequent SIAs when resources for a two-dose strategy are unavailable.

The impact of a physical geographic barrier on the dynamics of measles.

Spatial-temporal patterns of measles incidence reflect the spatial distribution of human hosts. The heterogeneous spatial distribution of communities has been shown to introduce spatially dependent temporal lags in the timing of measles incidence. Incidence patterns reflect internal dynamics within a community and coupling of communities through the movement of infectious individuals. The central role of human movement in coupling dynamics in separate communities suggests that physical geographic barriers to movement should reduce spatial-temporal correlation. We examine measles dynamics in Maryland and Pennsylvania during the period of 1917-1938. The central feature of interest is the Chesapeake Bay, which separates Maryland into two distinct regions. We find that correlation of measles incidences in communities separated by the bay is reduced compared to communities not separated by the bay, suggesting the bay acted as a barrier to human movement during this time sufficient to decouple measles dynamics in Maryland counties.