Lauren Gardner

Global risk of Zika virus depends critically on vector status of Aedes albopictus

1 recently pointed out that Zika virus has been collected from several mosquito species including those from the genera, Anopheles, Culex, and Mansonia besides Aedes. Moreover, at least ten Aedes species are known to harbour Zika virus. However, the presence of the virus does not automatically make the species an effi cient vector for the disease. It is, therefore, unfortunate that a recent risk map published in The Lancet considers Aedes aegypti and Aedes albopictus together. 2 On the same basis, WHO has predicted that the virus will establish itself in all countries in the Americas except Canada and Chile. 3

A Predictive Spatial Model to Quantify the Risk of Air-Travel-Associated Dengue Importation into the United States and Europe

The number of travel-acquired dengue infections has been on a constant rise in the United States and Europe over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue contributes to the increasing number of dengue cases. This paper reports results from a network-based regression model which uses international passenger travel volumes, travel distances, predictive species distribution models (for the vector species), and infection data to quantify the relative risk of importing travel-acquired dengue infections into the US and Europe from dengue-endemic regions. Given the necessary data, this model can be used to identify optimal locations (origin cities, destination airports, etc.) for dengue surveillance. The model can be extended to other geographical regions and vector-borne diseases, as well as other network-based processes.

A Systematic Review of the Comparative Epidemiology of Avian and Human Influenza A H5N1 and H7N9 – Lessons and Unanswered Questions

The aim of this work was to explore the comparative epidemiology of influenza viruses, H5N1 and H7N9, in both bird and human populations. Specifically, the article examines similarities and differences between the two viruses in their genetic characteristics, distribution patterns in human and bird populations and postulated mechanisms of global spread. In summary, H5N1 is pathogenic in birds, while H7N9 is not. Yet both have caused sporadic human cases, without evidence of sustained, human-to-human spread. The number of H7N9 human cases in the first year following its emergence far exceeded that of H5N1 over the same time frame. Despite the higher incidence of H7N9, the spatial distribution of H5N1 within a comparable time frame is considerably greater than that of H7N9, both within China and globally. The pattern of spread of H5N1 in humans and birds around the world is consistent with spread through wild bird migration and poultry trade activities. In contrast, human cases of H7N9 and isolations of H7N9 in birds and the environment have largely occurred in a number of contiguous provinces in south-eastern China. Although rates of contact with birds appear to be similar in H5N1 and H7N9 cases, there is a predominance of incidental contact reported for H7N9 as opposed to close, high-risk contact for H5N1. Despite the high number of human cases of H7N9 and the assumed transmission being from birds, the corresponding level of H7N9 virus in birds in surveillance studies has been low, particularly in poultry farms. H7N9 viruses are also diversifying at a much greater rate than H5N1 viruses. Analyses of certain H7N9 strains demonstrate similarities with engineered transmissible H5N1 viruses which make it more adaptable to the human respiratory tract. These differences in the human and bird epidemiology of H5N1 and H7N9 raise unanswered questions as to how H7N9 has spread, which should be investigated further.

A Global Airport-Based Risk Model for the Spread of Dengue Infection via the Air Transport Network

The number of travel-acquired dengue infections has seen a consistent global rise over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue has contributed to a rise in the number of dengue cases in both areas of endemicity and elsewhere. This paper reports results from a network-based risk assessment model which uses international passenger travel volumes, travel routes, travel distances, regional populations, and predictive species distribution models (for the two vector species, Aedes aegypti and Aedes albopictus) to quantify the relative risk posed by each airport in importing passengers with travel-acquired dengue infections. Two risk attributes are evaluated: (i) the risk posed by through traffic at each stopover airport and (ii) the risk posed by incoming travelers to each destination airport. The model results prioritize optimal locations (i.e., airports) for targeted dengue surveillance. The model is easily extendible to other vector-borne diseases.

Unanswered questions about the Middle East respiratory syndrome coronavirus (MERS-CoV)

BackgroundThe Middle East respiratory syndrome coronavirus (MERS-CoV) represents a current threat to the Arabian Peninsula, and potential pandemic disease. As of June 3, 2014, MERS CoV has reportedly infected 688 people and killed 282. We briefly summarize the state of the outbreak, and highlight unanswered questions and various explanations for the observed epidemiology.FindingsThe continuing but infrequent cases of MERS-CoV reported over the past two years have been puzzling and difficult to explain. The epidemiology of MERS-CoV, with many sporadic cases and a few hospital outbreaks, yet no sustained epidemic, suggests a low reproductive number. Furthermore, a clear source of infection to humans remains unknown. Also puzzling is the fact that MERS-CoV has been present in Saudi Arabia over several mass gatherings, including the 2012 and 2013 Hajj and Umrah pilgrimages, which predispose to epidemics, without an epidemic arising.ConclusionsThe observed epidemiology of MERS-CoV is quite distinct and does not clearly fit either a sporadic or epidemic pattern. Possible explanations of the unusual features of the epidemiology of MERS-CoV include sporadic ongoing infections from a non-human source; human to human transmission with a large proportion of undetected cases; or a combination of both. The virus has been identified in camels; however the mode of transmission of the virus to humans remains unknown, and many cases have no history of animal contact. In order to gain a better understanding of the epidemiology of MERS CoV, further investigation is warranted.

A Scenario-Based Evaluation of the Middle East Respiratory Syndrome Coronavirus and the Hajj

Between April 2012 and June 2014, 820 laboratory‐confirmed cases of the Middle East respiratory syndrome coronavirus (MERS‐CoV) have been reported in the Arabian Peninsula, Europe, North Africa, Southeast Asia, the Middle East, and the United States. The observed epidemiology is different to SARS, which showed a classic epidemic curve and was over in eight months. The much longer persistence of MERS‐CoV in the population, with a lower reproductive number, some evidence of human‐to‐human transmission but an otherwise sporadic pattern, is difficult to explain. Using available epidemiological data, we implemented mathematical models to explore the transmission dynamics of MERS‐CoV in the context of mass gatherings such as the Hajj pilgrimage, and found a discrepancy between the observed and expected epidemiology. The fact that no epidemic occurred in returning Hajj pilgrims in either 2012 or 2013 contradicts the long persistence of the virus in human populations. The explanations for this discrepancy include an ongoing, repeated nonhuman/sporadic source, a large proportion of undetected or unreported human‐to‐human cases, or a combination of the two. Furthermore, MERS‐CoV is occurring in a region that is a major global transport hub and hosts significant mass gatherings, making it imperative to understand the source and means of the yet unexplained and puzzling ongoing persistence of the virus in the human population.

Inferring Contagion Patterns in Social Contact Networks with Limited Infection Data

The spread of infectious disease is an inherently stochastic process. As such, real time control and prediction methods present a significant challenge. For diseases which spread through direct human interaction, (e.g., transferred from infected to susceptible individuals) the contagion process can be modeled on a social-contact network where individuals are represented as nodes, and contacts between individuals are represented as links. The model presented in this paper seeks to identify the infection pattern which depicts the current state of an ongoing outbreak. This is accomplished by inferring the most likely paths of infection through a contact network under the assumption of partially available infection data. The problem is formulated as a bi-linear integer program, and heuristic solution methods are developed based on sub-problems which can be solved much more efficiently. The heuristic performance is presented for a range of randomly generated networks and different levels of information. The model results, which include the most likely set of infection spreading contacts, can be used to provide insight into future epidemic outbreak patterns, and aid in the development of intervention strategies.

Vector status of Aedes species determines geographical risk of autochthonous Zika virus establishment

Background The 2015-16 Zika virus pandemic originating in Latin America led to predictions of a catastrophic global spread of the disease. Since the current outbreak began in Brazil in May 2015 local transmission of Zika has been reported in over 60 countries and territories, with over 750 thousand confirmed and suspected cases. As a result of its range expansion attention has focused on possible modes of transmission, of which the arthropod vector-based disease spread cycle involving Aedes species is believed to be the most important. Additional causes of concern are the emerging new links between Zika disease and Guillain-Barre Syndrome (GBS), and a once rare congenital disease, microcephaly. Methodology/principal findings Like dengue and chikungunya, the geographic establishment of Zika is thought to be limited by the occurrence of its principal vector mosquito species, Ae. aegypti and, possibly, Ae. albopictus. While Ae. albopictus populations are more widely established than those of Ae. aegypti, the relative competence of these species as a Zika vector is unknown. The analysis reported here presents a global risk model that considers the role of each vector species independently, and quantifies the potential spreading risk of Zika into new regions. Six scenarios are evaluated which vary in the weight assigned to Ae. albopictus as a possible spreading vector. The scenarios are bounded by the extreme assumptions that spread is driven by air travel and Ae. aegypti presence alone and spread driven equally by both species. For each scenario destination cities at highest risk of Zika outbreaks are prioritized, as are source cities in affected regions. Finally, intercontinental air travel routes that pose the highest risk for Zika spread are also ranked. The results are compared between scenarios. Conclusions/significance Results from the analysis reveal that if Ae. aegypti is the only competent Zika vector, then risk is geographically limited; in North America mainly to Florida and Texas. However, if Ae. albopictus proves to be a competent vector of Zika, which does not yet appear to be the case, then there is risk of local establishment in all American regions including Canada and Chile, much of Western Europe, Australia, New Zealand, as well as South and East Asia, with a substantial increase in risk to Asia due to the more recent local establishment of Zika in Singapore.

Inferring Contagion Patterns in Social Contact Networks Using a Maximum Likelihood Approach

AbstractThe spread of infectious disease is an inherently stochastic process. As such, real-time control and prediction methods present a significant challenge. For diseases that spread through direct human interaction, the contagion process can be modeled on a social contact network where individuals are represented as nodes, and contact between individuals is represented as links. The objective of the model described in this paper is to infer the most likely path of infection through a contact network for an ongoing outbreak. The problem is formulated as a linear integer program. Specific properties of the problem are exploited to develop a much more efficient solution method than solving the linear program directly. The model output can provide insight into future epidemic outbreak patterns and aid in the development of intervention strategies. The model is evaluated for a combination of network structures and sizes, as well as various disease properties and potential human error in assessing these pro...

Risk of Dengue Spread from the Philippines Through International Air Travel

Epidemics of dengue fever occur every 3 to 4 years in the Philippines. The risk of a dengue fever outbreak in the Philippines has been heightened since Typhoon Haiyan struck the region in November 2013 because recovery efforts have been slow to progress. The structural damage caused by the typhoon resulted in an abundance of standing water, which can serve as mosquito breeding grounds. Should an outbreak of dengue occur, infected travelers departing the Philippines pose a risk because they may introduce the dengue virus into local vector populations (of Aedes aegypti and Aedes albopictus) at their destinations. This study quantifies the risk posed by potentially infected travelers departing the Philippines by using a network model that incorporates predictive species distribution models, demographic features of destination areas, and air traffic volumes. The analysis reveals that a majority of travelers departing Philippine airports deplane in regions suitable for harboring Aedes aegypti or Aedes albopictus; this factor increases the likelihood of further spread of the disease if an outbreak were to occur. Because it is impractical to implement all possible monitoring and control measures at all locations connected to the Philippines, this analysis ranks the set of candidates and thus allows surveillance resources to be optimally deployed.