Dynamics of dengue epidemics in urban contexts

"Dengue fever is not just urban or rural: Reframing its spatial categorization."

Infectious diseases exploit niches that are often spatially defined as urban and/or rural. Yet spatial research on infectious diseases often fails to define "urban" and "rural" and how these contexts might influence their epidemiology. We use dengue fever, thought to be mostly an urban disease with rural foci, as a device to explore local definitions of urban and rural spaces and the impact of these spaces on dengue risk in the province of Esmeraldas, Ecuador. Ecuador, like many countries, only uses population size and administrative function to define urban and rural locales. Interviews conducted from 2019 to 2021 with 71 residents and 23 health personnel found that they identified the availability of basic services, extent of their control over their environment, and presence of underbrush and weeds (known in Ecuador as monte and maleza and conceptualized in this paper as natural disorder) as important links to their conceptions of space and dengue risk. This broader conceptualization of space articulated by local residents and professionals reflects a more sophisticated approach to characterizing dengue risk than using categories of urban and rural employed by the national census and government. Rather than this dichotomous category of space, dengue fever can be better framed for health interventions in terms of specific environmental features and assemblages of high-risk spaces. An understanding of how community members perceive risk enhances our ability to collaborate with them to develop optimal mitigation strategies.

A model based on cellular automata to estimate the social isolation impact on COVID-19 spreading in Brazil

Background and objective Many countries around the world experienced a high increase in the number of COVID-19 cases after a few weeks of the first case, and along with it, excessive pressure on the healthcare systems. While medicines, drugs, and vaccines against the COVID-19 are being developed, social isolation has become the most used method for controlling the virus spreading. With the social isolation, authorities aimed to slow down the spreading, avoiding saturation of the healthcare system, and allowing that all critical COVID-19 cases could be appropriately treated. By tuning the proposed model to fit Brazil's initial COVID-19 data, the objectives of the paper are to analyze the impact of the social isolation features on the population dynamics; simulate the number of deaths due to COVID-19 and due to the lack of healthcare infrastructure; study combinations of the features for the healthcare system does not collapse; and analyze healthcare system responses for the crisis. Methods In this paper, a Susceptible-Exposed-Infected-Removed model is described in terms of probabilistic cellular automata and ordinary differential equations for the transmission of COVID-19, flexible enough for simulating different scenarios of social isolation according to the following features: the start day for the social isolation after the first death, the period for the social isolation campaign, and the percentage of the population committed to the campaign. Results Results showed that efforts in the social isolation campaign must be concentrated both on the isolation percentage and campaign duration to delay the healthcare system failure. For the hospital situation in Brazil at the beginning of the pandemic outbreak, a rate of 200 purchases per day of intensive care units and mechanical ventilators is the minimum rate to prevent the collapse of the healthcare system. Conclusions By using the model for different scenarios, it is possible to estimate the impact of social isolation campaign adhesion. For instance, if the social isolation percentage increased from 40% to 50% in Brazil, the purchase rate of 150 intensive care units and mechanical ventilators per day would be enough to prevent the healthcare system to collapse. Moreover, results showed that a premature relaxation of the social isolation campaign can lead to subsequent waves of contamination.

Protective Immunity to Dengue Virus Induced by DNA Vaccines Encoding Nonstructural Proteins in a Lethal Challenge Immunocompetent Mouse Model

Dengue virus represents the main arbovirus affecting humans, but there are no effective drugs or available worldwide licensed vaccine formulations capable of conferring full protection against the infection. Experimental studies and results generated after the release of the licensed anti-DENV vaccine demonstrated that induction of high-titer neutralizing antibodies does not represent the sole protection correlate and that, indeed, T cell-based immune responses plays a relevant role in the establishment of an immune protective state. In this context, this study aimed to further demonstrate protective features of immune responses elicited in immunocompetent C57BL/6 mice immunized with three plasmids encoding DENV2 nonstructural proteins (NS1, NS3, and NS5), which were subsequently challenged with a DENV2 strain naturally capable of inducing lethal encephalitis in immunocompetent mouse strains. The animals were immunized intramuscularly with the DNA vaccine mix and complete protection was observed among vaccinated mice. Vaccine induced protection correlated with the cytokine profiles expressed by spleen cells and brain-infiltrating mononuclear cells. The results confirm the pivotal role of cellular immune responses targeting nonstructural DENV proteins and validate the experimental model based on a DENV2 strain capable of infecting and killing immunocompetent mice as a tool for the evaluation of protective immunity induced by anti-DENV vaccines.

NS1 Recombinant Proteins Are Efficiently Produced in Pichia pastoris and Have Great Potential for Use in Diagnostic Kits for Dengue Virus Infections

Dengue is one of the major diseases causing global public health concerns. Despite technological advances in vaccine production against all its serotypes, it is estimated that the dengue virus is responsible for approximately 390 million infections per year. Laboratory diagnosis has been the key point for the correct treatment and prevention of this disease. Currently, the limiting factor in the manufacture of dengue diagnostic kits is the large-scale production of the non-structural 1 (NS1) antigen used in the capture of the antibody present in the infected patients' serum. In this work, we demonstrate the production of the non-structural 1 protein of dengue virus (DENV) serotypes 1-4 (NS1-DENV1, NS1-DENV2, NS1-DENV3, and NS1-DENV4) in the methylotrophic yeast Pichia pastoris KM71H. Secreted recombinant protein was purified by affinity chromatography and characterized by SDS-PAGE and ELISA. The objectives of this study were achieved, and the results showed that P. pastoris is a good heterologous host and worked well in the production of NS1DENV 1-4 recombinant proteins. Easy to grow and quick to obtain, this yeast secreted ready-to-use proteins, with a final yield estimated at 2.8-4.6 milligrams per liter of culture. We reached 85-91% sensitivity and 91-93% specificity using IgM as a target, and for anti-dengue IgG, 83-87% sensitivity and 81-93% specificity were achieved. In this work, we conclude that the NS1 recombinant proteins are efficiently produced in P. pastoris and have great potential for use in diagnostic kits for dengue virus infections. The transformed yeast obtained can be used for production in industrial-scale bioreactors.

Modeling the Heterogeneity of Dengue Transmission in a City

Dengue fever is one of the most important vector-borne diseases in the world, and modeling its transmission dynamics allows for determining the key influence factors and helps to perform interventions. The heterogeneity of mosquito bites of humans during the spread of dengue virus is an important factor that should be considered when modeling the dynamics. However, traditional models generally assumed homogeneous mixing between humans and vectors, which is inconsistent with reality. In this study, we proposed a compartmental model with negative binomial distribution transmission terms to model this heterogeneity at the population level. By including the aquatic stage of mosquitoes and incorporating the impacts of the environment and climate factors, an extended model was used to simulate the 2014 dengue outbreak in Guangzhou, China, and to simulate the spread of dengue in different scenarios. The results showed that a high level of heterogeneity can result in a small peak size in an outbreak. As the level of heterogeneity decreases, the transmission dynamics approximate the dynamics predicted by the corresponding homogeneous mixing model. The simulation results from different scenarios showed that performing interventions early and decreasing the carrying capacity for mosquitoes are necessary for preventing and controlling dengue epidemics. This study contributes to a better understanding of the impact of heterogeneity during the spread of dengue virus.

Dynamics of dengue disease with human and vector mobility

Dengue is a vector borne disease transmitted to humans by Aedes aegypti mosquitoes carrying virus of different serotypes. Dengue exhibits complex spatial and temporal dynamics, influenced by various biological, human and environmental factors. In this work, we study the dengue spread for a single serotype (DENV-1) including statistical models of human mobility with exponential step length distribution, by using reaction-diffusion equations and Stochastic Cellular Automata (SCA) approach. We analyze the spatial and temporal spreading of the disease using parameters from field studies. We choose mosquito density data from Ahmedabad city as a proxy for climate data in our SCA model. We find an interesting result that although human mobility makes the infection spread faster, there is an apparent early suppression of the epidemic compared to immobile humans. The disease extinction time is lesser when human mobility is included.

Day-to-Day Population Movement and the Management of Dengue Epidemics

Dengue is a growing public health problem in tropical and subtropical cities. It is transmitted by mosquitoes, and the main strategy for epidemic prevention and control is insecticide fumigation. Effective management is, however, proving elusive. People’s day-to-day movement about the city is believed to be an important factor in the epidemiological dynamics. We use a simple model to examine the fundamental roles of broad demographic and spatial structures in epidemic initiation, growth and control. We show that the key factors are local dilution, characterised by the vector–host ratio, and spatial connectivity, characterised by the extent of habitually variable movement patterns. Epidemic risk in the population is driven by the demographic groups that frequent the areas with the highest vector–host ratio, even if they only spend some of their time there. Synchronisation of epidemic trajectories in different demographic groups is governed by the vector–host ratios to which they are exposed and the strength of connectivity. Strategies for epidemic prevention and management may be made more effective if they take into account the fluctuating landscape of transmission intensity associated with spatial heterogeneity in the vector–host ratio and people’s day-to-day movement patterns.

Emergence of Epidemic Dengue-1 Virus in the Southern Province of Sri Lanka

BACKGROUND

Dengue is a frequent cause of acute febrile illness with an expanding global distribution. Since the 1960s, dengue in Sri Lanka has been documented primarily along the heavily urbanized western coast with periodic shifting of serotypes. Outbreaks from 2005-2008 were attributed to a new clade of DENV-3 and more recently to a newly introduced genotype of DENV-1. In 2007, we conducted etiologic surveillance of acute febrile illness in the Southern Province and confirmed dengue in only 6.3% of febrile patients, with no cases of DENV-1 identified. To re-evaluate the importance of dengue as an etiology of acute febrile illness in this region, we renewed fever surveillance in the Southern Province to newly identify and characterize dengue.

METHODOLOGY/PRINCIPAL FINDINGS

A cross-sectional surveillance study was conducted at the largest tertiary care hospital in the Southern Province from 2012-2013. A total of 976 patients hospitalized with acute undifferentiated fever were enrolled, with 64.3% male and 31.4% children. Convalescent blood samples were collected from 877 (89.6%). Dengue virus isolation, dengue RT-PCR, and paired IgG ELISA were performed. Acute dengue was confirmed as the etiology for 388 (39.8%) of 976 hospitalizations, with most cases (291, 75.0%) confirmed virologically and by multiple methods. Among 351 cases of virologically confirmed dengue, 320 (91.2%) were due to DENV-1. Acute dengue was associated with self-reported rural residence, travel, and months having greatest rainfall. Sequencing of selected dengue viruses revealed that sequences were most closely related to those described from China and Southeast Asia, not nearby India.

CONCLUSIONS/SIGNIFICANCE

We describe the first epidemic of DENV-1 in the Southern Province of Sri Lanka in a population known to be susceptible to this serotype because of prior study. Dengue accounted for 40% of acute febrile illnesses in the current study. The emergence of DENV-1 as the foremost serotype in this densely populated but agrarian population highlights the changing epidemiology of dengue and the need for continued surveillance and prevention.

Production of a Recombinant Dengue Virus 2 NS5 Protein and Potential Use as a Vaccine Antigen

Dengue fever is caused by any of the four known dengue virus serotypes (DENV1 to DENV4) that affect millions of people worldwide, causing a significant number of deaths. There are vaccines based on chimeric viruses, but they still are not in clinical use. Anti-DENV vaccine strategies based on nonstructural proteins are promising alternatives to those based on whole virus or structural proteins. The DENV nonstructural protein 5 (NS5) is the main target of anti-DENV T cell-based immune responses in humans. In this study, we purified a soluble recombinant form of DENV2 NS5 expressed in Escherichia coli at large amounts and high purity after optimization of expression conditions and purification steps. The purified DENV2 NS5 was recognized by serum from DENV1-, DENV2-, DENV3-, or DENV4-infected patients in an epitope-conformation-dependent manner. In addition, immunization of BALB/c mice with NS5 induced high levels of NS5-specific antibodies and expansion of gamma interferon- and tumor necrosis factor alpha-producing T cells. Moreover, mice immunized with purified NS5 were partially protected from lethal challenges with the DENV2 NGC strain and with a clinical isolate (JHA1). These results indicate that the recombinant NS5 protein preserves immunological determinants of the native protein and is a promising vaccine antigen capable of inducing protective immune responses.

Testing the impact of virus importation rates and future climate change on dengue activity in Malaysia using a mechanistic entomology and disease model

We aimed to reparameterize and validate an existing dengue model, comprising an entomological component (CIMSiM) and a disease component (DENSiM) for application in Malaysia. With the model we aimed to measure the effect of importation rate on dengue incidence, and to determine the potential impact of moderate climate change (a 1 °C temperature increase) on dengue activity. Dengue models (comprising CIMSiM and DENSiM) were reparameterized for a simulated Malaysian village of 10 000 people, and validated against monthly dengue case data from the district of Petaling Jaya in the state of Selangor. Simulations were also performed for 2008-2012 for variable virus importation rates (ranging from 1 to 25 per week) and dengue incidence determined. Dengue incidence in the period 2010-2012 was modelled, twice, with observed daily weather and with a 1 °C increase, the latter to simulate moderate climate change. Strong concordance between simulated and observed monthly dengue cases was observed (up to r = 0·72). There was a linear relationship between importation and incidence. However, a doubling of dengue importation did not equate to a doubling of dengue activity. The largest individual dengue outbreak was observed with the lowest dengue importation rate. Moderate climate change resulted in an overall decrease in dengue activity over a 3-year period, linked to high human seroprevalence early on in the simulation. Our results suggest that moderate reductions in importation with control programmes may not reduce the frequency of large outbreaks. Moderate increases in temperature do not necessarily lead to greater dengue incidence.

Practices of Dengue Fever Prevention and the Associated Factors among the Orang Asli in Peninsular Malaysia

BACKGROUND

Dengue is prevalent among Malaysia's indigenous peoples, known as the Orang Asli, and it poses a serious health threat to them. The study aims to look at the socio-demographic factors, health beliefs, and knowledge about dengue and its association to dengue prevention practices among Orang Asli communities in Peninsular Malaysia.

METHODS

A cross-sectional survey was conducted in 16 randomly selected Orang Asli villages from eight states in Peninsular Malaysia from April 2012 until February 2013.

RESULTS

A total of 560 Orang Asli were interviewed and 505 completed the survey. Slightly above half of the participants (n = 280, 55.4%) had a total dengue prevention score of 51-100 (of a possible score of 0-100). Multivariate analysis findings showed dengue knowledge, perceived barriers to perform dengue prevention, fogging frequency, and perceived susceptibility to dengue fever as significant factors associated to dengue prevention practices. Participants with a lower dengue knowledge score (score 0-18) were less likely (OR = 0.63, 95%CI = 0.44-0.92 vs. score 19-36, P = 0.015) to practice dengue prevention. Participants with low perceived barriers to prevent dengue (score of 1-5) were more likely (OR = 2.06, 95%CI = 1.21-3.53, vs. score of 6-10, P = 0.008) to practice dengue prevention. Villages that were not fogged (OR = 0.49, 95%CI = 0.24-0.99, P = 0.045) or rarely fogged (OR = 0.40, 95%CI = 0.22-0.75, P = 0.004) had lower dengue prevention practices than villages that were fogged often. Participants with low perceived susceptibility of acquiring dengue (score of 1-5) were less likely (OR = 0.54, 95%CI = 0.33-0.89 vs. score of 6-10, P = 0.018) to practice dengue prevention measures.

CONCLUSION

Findings imply that educational and health programmes should focus on enhancing dengue knowledge and perceived susceptibility of acquiring dengue and reducing perceived barriers to performing dengue prevention practices among the Orang Asli. More outreach on mosquito control campaigns should be carried out especially in villages where mosquito fogging is frequent.

Economic Burden of Dengue Virus Infection at the Household Level Among Residents of Puerto Maldonado, Peru

Dengue virus (DENV) was reintroduced to Peru in the 1990s and has been reported in Puerto Maldonado (population ~65,000) in the Peruvian southern Amazon basin since 2000. This region also has the highest human migration rate in the country, mainly from areas not endemic for DENV. The objective of this study was to assess the proportion of household income that is diverted to costs incurred because of dengue illness and to compare these expenses between recent migrants (RMs) and long-term residents (LTRs). We administered a standardized questionnaire to persons diagnosed with dengue illness at Hospital Santa Rosa in Puerto Maldonado from December 2012 to March 2013. We compared direct and indirect medical costs between RMs and LTRs. A total of 80 participants completed the survey, of whom 28 (35%) were RMs and 52 (65%) were LTRs. Each dengue illness episode cost the household an average of US$105 (standard deviation [SD] = 107), representing 24% of their monthly income. Indirect costs were the greatest expense (US$56, SD = 87), especially lost wages. The proportion of household income diverted to dengue illness did not differ significantly between RM and LTR households. The study highlights the significant financial burden incurred by households when a family member suffers dengue illness.

A spatial simulation model for dengue virus infection in urban areas

Background

The World Health Organization estimates that the global number of dengue infections range between 80–100 million per year, with some studies estimating approximately three times higher numbers. Furthermore, the geographic range of dengue virus transmission is extending with the disease now occurring more frequently in areas such as southern Europe. Ae. aegypti, one of the most prominent dengue vectors, is endemic to the far north-east of Australia and the city of Cairns frequently experiences dengue outbreaks which sometimes lead to large epidemics.

Method

A spatially-explicit, individual-based mathematical model that accounts for the spread of dengue infection as a result of human movement and mosquito dispersion is presented. The model closely couples the four key sub-models necessary for representing the overall dynamics of the physical system, namely those describing mosquito population dynamics, human movement, virus transmission and vector control. Important features are the use of high quality outbreak data and mosquito trapping data for calibration and validation and a strategy to derive local mosquito abundance based on vegetation coverage and census data.

Results

The model has been calibrated using detailed 2003 dengue outbreak data from Cairns, together with census and mosquito trapping data, and is shown to realistically reproduce a further dengue outbreak. The simulation results replicating the 2008/2009 Cairns epidemic support several hypotheses (formulated previously) aimed at explaining the large-scale epidemic which occurred in 2008/2009; specifically, while warmer weather and increased human movement had only a small effect on the spread of the virus, a shorter virus strain-specific extrinsic incubation time can explain the observed explosive outbreak of 2008/2009.

Conclusion

The proof-of-concept simulation model described in this study has potential as a tool for understanding factors contributing to dengue spread as well as planning and optimizing dengue control, including reducing the Ae. aegypti vector population and for estimating the effectiveness and cost-effectiveness of future vaccination programmes. This model could also be applied to other vector borne viral diseases such as chikungunya, also spread by Ae. aegypti and, by re-parameterisation of the vector sub-model, to dengue and chikungunya viruses spread by Aedes albopictus.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2334-14-447) contains supplementary material, which is available to authorized users.

Emergence and prevalence of human vector-borne diseases in sink vector populations

Vector-borne diseases represent a major public health concern in most tropical and subtropical areas, and an emerging threat for more developed countries. Our understanding of the ecology, evolution and control of these diseases relies predominantly on theory and data on pathogen transmission in large self-sustaining ‘source’ populations of vectors representative of highly endemic areas. However, there are numerous places where environmental conditions are less favourable to vector populations, but where immigration allows them to persist. We built an epidemiological model to investigate the dynamics of six major human vector borne-diseases in such non self-sustaining ‘sink’ vector populations. The model was parameterized through a review of the literature, and we performed extensive sensitivity analysis to look at the emergence and prevalence of the pathogen that could be encountered in these populations. Despite the low vector abundance in typical sink populations, all six human diseases were able to spread in 15–55% of cases after accidental introduction. The rate of spread was much more strongly influenced by vector longevity, immigration and feeding rates, than by transmission and virulence of the pathogen. Prevalence in humans remained lower than 5% for dengue, leishmaniasis and Japanese encephalitis, but substantially higher for diseases with longer duration of infection; malaria and the American and African trypanosomiasis. Vector-related parameters were again the key factors, although their influence was lower than on pathogen emergence. Our results emphasize the need for ecology and evolution to be thought in the context of metapopulations made of a mosaic of sink and source habitats, and to design vector control program not only targeting areas of high vector density, but working at a larger spatial scale.

Modelling bluetongue virus transmission between farms using animal and vector movements

Bluetongue is a notifiable disease of ruminants which, in 2007, occurred for the first time in England. We present the first model for bluetongue that explicitly incorporates farm to farm movements of the two main hosts, as well as vector dispersal. The model also includes a seasonal vector to host ratio and dynamic restriction zones that evolve as infection is detected. Batch movements of sheep were included by modelling degree of mixing at markets. We investigate the transmission of bluetongue virus between farms in eastern England (the focus of the outbreak). Results indicate that most parameters affecting outbreak size relate to vectors and that the infection generally cannot be maintained without between-herd vector transmission. Movement restrictions are effective at reducing outbreak size, and a targeted approach would be as effective as a total movement ban. The model framework is flexible and can be adapted to other vector-borne diseases of livestock.

Hospital-based prevalence of malaria and dengue in febrile patients in Bangladesh

We conducted a nationwide study at six tertiary hospitals from December 2008 through November 2009 to investigate etiologies of febrile illnesses in Bangladesh. Febrile patients meeting a clinical case definition were enrolled from inpatient and outpatient medicine and pediatric units. We assessed 720 febrile patients over 12 months; 69 (9.6%) were positive for IgM antibodies against dengue virus by enzyme-linked immunosorbent assay, and four malaria patients (0.56%) were confirmed with immuno-chromatography and microscopic slide tests. We identified dengue cases throughout the year from rural (49%) and urban areas (51%). We followed-up 55 accessible dengue-infected patients two months after their initial enrollment: 45 (82%) patients had fully recovered, 9 (16%) reported ongoing jaundice, fever and/or joint pain, and one died. Dengue infection is widespread across Bangladesh, but malaria is sufficiently uncommon that it should not be assumed as the cause of fever without laboratory confirmation.

Dengue epidemics and human mobility

In this work we explore the effects of human mobility on the dispersion of a vector borne disease. We combine an already presented stochastic model for dengue with a simple representation of the daily motion of humans on a schematic city of 20 × 20 blocks with 100 inhabitants in each block. The pattern of motion of the individuals is described in terms of complex networks in which links connect different blocks and the link length distribution is in accordance with recent findings on human mobility. It is shown that human mobility can turn out to be the main driving force of the disease dispersal.

Modeling the dynamic transmission of dengue fever: investigating disease persistence

BACKGROUND

Dengue is a disease of great complexity, due to interactions between humans, mosquitoes and various virus serotypes as well as efficient vector survival strategies. Thus, understanding the factors influencing the persistence of the disease has been a challenge for scientists and policy makers. The aim of this study is to investigate the influence of various factors related to humans and vectors in the maintenance of viral transmission during extended periods.

METHODOLOGY/PRINCIPAL FINDINGS

We developed a stochastic cellular automata model to simulate the spread of dengue fever in a dense community. Each cell can correspond to a built area, and human and mosquito populations are individually monitored during the simulations. Human mobility and renewal, as well as vector infestation, are taken into consideration. To investigate the factors influencing the maintenance of viral circulation, two sets of simulations were performed: (1(st)) varying human renewal rates and human population sizes and (2(nd)) varying the house index (fraction of infested buildings) and vector per human ratio. We found that viral transmission is inhibited with the combination of small human populations with low renewal rates. It is also shown that maintenance of viral circulation for extended periods is possible at low values of house index. Based on the results of the model and on a study conducted in the city of Recife, Brazil, which associates vector infestation with Aedes aegytpi egg counts, we question the current methodology used in calculating the house index, based on larval survey.

CONCLUSIONS/SIGNIFICANCE

This study contributed to a better understanding of the dynamics of dengue subsistence. Using basic concepts of metapopulations, we concluded that low infestation rates in a few neighborhoods ensure the persistence of dengue in large cities and suggested that better strategies should be implemented to obtain measures of house index values, in order to improve the dengue monitoring and control system.

Refolded dengue virus type 2 NS1 protein expressed in Escherichia coli preserves structural and immunological properties of the native protein

The dengue virus NS1 protein has been shown to be a protective antigen under different experimental conditions but the recombinant protein produced in bacterial expression systems is usually not soluble and loses structural and immunological features of the native viral protein. In the present study, experimental conditions leading to purification and refolding of the recombinant dengue virus type 2 (DENV-2) NS1 protein expressed in Escherichia coli are described. The refolded recombinant protein was recovered as heat-stable soluble dimers with preserved structural features, as demonstrated by spectroscopic methods. In addition, antibodies against epitopes of the NS1 protein expressed in eukaryotic cells recognized the refolded protein expressed in E. coli but not the denatured form or the same protein submitted to a different refolding condition. Collectively, the results demonstrate that the recombinant NS1 protein preserved important conformation and antigenic determinants of the native virus protein and represents a valuable reagent either for the development of vaccines or for diagnostic methods.

Health research based on geospatial tools: a timely approach in a changing environment

The possibilities of disease prediction based on the environmental characteristics of geographical areas and specific requirements of the causative infectious agents are reviewed and, in the case of parasites whose life cycles involve more than one host, the needs of the intermediate hosts are also referred to. The geographical information systems framework includes epidemiological data, visualization (in the form of maps), modelling and exploratory analysis using spatial statistics. Examples include climate-based forecast systems, based on the concept of growing degree days, which now exist for several parasitic helminths such as fasciolosis, schistosomiasis, dirofilariasis and also for malaria. The paper discusses the limits of data collection by remote sensing in terms of resolution capabilities (spatial, temporal and spectral) of sensors on-board satellites. Although the data gained from the observation of oceans, land, elevations, land cover, land use, surface temperatures, rainfall, etc. are primarily for weather forecasting, military and commercial use, some of this information, particularly that from the climate research satellites, is of direct epidemiological utility. Disease surveillance systems and early-warning systems (EWS) are prime examples of academic approaches of practical importance. However, even commercial activities such as the construction of virtual globes, i.e. computer-based models of the Earth, have been used in this respect. Compared to conventional world maps, they do not only show geographical and man-made features, but can also be spatially annotated with data on disease distribution, demography, economy and other measures of particular interest.

The role of human movement in the transmission of vector-borne pathogens

Background

Human movement is a key behavioral factor in many vector-borne disease systems because it influences exposure to vectors and thus the transmission of pathogens. Human movement transcends spatial and temporal scales with different influences on disease dynamics. Here we develop a conceptual model to evaluate the importance of variation in exposure due to individual human movements for pathogen transmission, focusing on mosquito-borne dengue virus.

Methodology and Principal Findings

We develop a model showing that the relevance of human movement at a particular scale depends on vector behavior. Focusing on the day-biting Aedes aegypti, we illustrate how vector biting behavior combined with fine-scale movements of individual humans engaged in their regular daily routine can influence transmission. Using a simple example, we estimate a transmission rate (R₀) of 1.3 when exposure is assumed to occur only in the home versus 3.75 when exposure at multiple locations—e.g., market, friend's—due to movement is considered. Movement also influences for which sites and individuals risk is greatest. For the example considered, intriguingly, our model predicts little correspondence between vector abundance in a site and estimated R₀ for that site when movement is considered. This illustrates the importance of human movement for understanding and predicting the dynamics of a disease like dengue. To encourage investigation of human movement and disease, we review methods currently available to study human movement and, based on our experience studying dengue in Peru, discuss several important questions to address when designing a study.

Conclusions/Significance

Human movement is a critical, understudied behavioral component underlying the transmission dynamics of many vector-borne pathogens. Understanding movement will facilitate identification of key individuals and sites in the transmission of pathogens such as dengue, which then may provide targets for surveillance, intervention, and improved disease prevention.

Vector-borne diseases constitute a largely neglected and enormous burden on public health in many resource-challenged environments, demanding efficient control strategies that could be developed through improved understanding of pathogen transmission. Human movement—which determines exposure to vectors—is a key behavioral component of vector-borne disease epidemiology that is poorly understood. We develop a conceptual framework to organize past studies by the scale of movement and then examine movements at fine-scale—i.e., people going through their regular, daily routine—that determine exposure to insect vectors for their role in the dynamics of pathogen transmission. We develop a model to quantify risk of vector contact across locations people visit, with emphasis on mosquito-borne dengue virus in the Amazonian city of Iquitos, Peru. An example scenario illustrates how movement generates variation in exposure risk across individuals, how transmission rates within sites can be increased, and that risk within sites is not solely determined by vector density, as is commonly assumed. Our analysis illustrates the importance of human movement for pathogen transmission, yet little is known—especially for populations most at risk to vector-borne diseases (e.g., dengue, leishmaniasis, etc.). We outline several important considerations for designing epidemiological studies to encourage investigation of individual human movement, based on experience studying dengue.