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

Chikungunya: a reemerging infection spreading during 2010 dengue fever outbreak in National Capital Region of India

Chikungunya fever is an important reemerging arbovirus illness, which is transmitted by the same vector as of dengue virus. Many cases of concurrent infections with multiple dengue virus serotypes have been reported in many countries. Also, concurrent infection with Chikungunya virus and dengue virus has been reported in the past in Delhi. Therefore, this study was done to detect Chikungunya IgM antibodies in suspected dengue fever patients. In this study, 1666 serum samples suspected of dengue fever and collected during the outbreak period (August 2010-December 2010) were tested for dengue IgM antibodies, of which 736 tested negative. Of the 736 dengue IgM negative sera, 666 were tested for Chikungunya IgM antibodies. The demographic profile and essential laboratory investigations were recorded. Chikungunya IgM was detected in 9.91 % of the patients. During the post-monsoon period though dengue dominated in numbers, the number of Chikungunya fever cases increased gradually followed by an abrupt decrease with the onset of winter. The Chikungunya IgM positive patients were suffering from fever of more than 5 days duration and had thrombocytopenia. Due to similarity in clinical features and vector transmitting dengue and Chikungunya virus, continuous surveillance of both dengue fever and Chikungunya fever is desirable for better management and epidemiological assessment.

Dengue and chikungunya: modelling the expansion of mosquito-borne viruses into naïve populations

With the recent global spread of a number of mosquito-borne viruses, there is an urgent need to understand the factors that contribute to the ability of viruses to expand into naïve populations. Using dengue and chikungunya viruses as case studies, we detail the necessary components of the expansion process: presence of the mosquito vector; introduction of the virus; and suitable conditions for local transmission. For each component we review the existing modelling approaches that have been used to understand recent emergence events or to assess the risk of future expansions. We identify gaps in our knowledge that are related to each of the distinct aspects of the human-mosquito transmission cycle: mosquito ecology; human-mosquito contact; mosquito-virus interactions; and human-virus interactions. Bridging these gaps poses challenges to both modellers and empiricists, but only through further integration of models and data will we improve our ability to better understand, and ultimately control, several infectious diseases that exert a significant burden on human health.

Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data

Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. Data describing human mobility and malaria epidemiology can help classify landscapes into parasite demographic sources and sinks, ecological concepts that have parallels in malaria control discussions of transmission foci. By linking transmission to parasite flow, it is possible to stratify landscapes for malaria control and elimination, as sources are disproportionately important to the regional persistence of malaria parasites. Here, we identify putative malaria sources and sinks for pre-elimination Namibia using malaria parasite rate (PR) maps and call data records from mobile phones, using a steady-state analysis of a malaria transmission model to infer where infections most likely occurred. We also examined how the landscape of transmission and burden changed from the pre-elimination setting by comparing the location and extent of predicted pre-elimination transmission foci with modeled incidence for 2009. This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. The changing spatial distribution of burden could be due to importation, with cases focused around importation hotspots, or due to heterogeneous application of elimination effort. While this framework is an important step towards understanding progressive changes in malaria distribution and the role of subnational transmission dynamics in a policy-relevant way, future work should account for international parasite movement, utilize real time surveillance data, and relax the steady state assumption required by the presented model.

For countries considering pursuing malaria elimination, understanding where malaria transmission occurs is crucial for intervention planning. By identifying the areas that act as sources of malaria parasites, elimination programs can target efforts to end local transmission and achieve nationwide elimination. Mapping parasite sources requires a modeling framework that integrates malaria burden and human movement information, however, as human mobility facilitates parasite spread and drives source-sink disease dynamics. In this study, we present a mathematical model that can be used to identify areas with self-sustaining malaria transmission when analyzed at equilibrium. We demonstrate how this method can inform elimination planning for countries with stable low transmission using data from Namibia. The maps of sources and sinks created using this method can be used to direct policy and target areas with self-sustaining malaria transmission in countries with stable transmission. Finally, we compare the predicted extent of transmission foci with more recent maps of incidence, to determine whether local transmission likely retreated into focal areas and the potential importance of importation.

Does insecticide resistance contribute to heterogeneities in malaria transmission in The Gambia?

BACKGROUND

Malaria hotspots, areas with consistently higher than average transmission, may become increasingly common as malaria declines. This phenomenon, currently observed in The Gambia, may be caused by several factors, including some related to the local vectors, whose contribution is poorly understood.

METHODS

Using WHO susceptibility bioassays, insecticide resistance status was determined in vector populations sampled from six pairs of villages across The Gambia, each pair contained a low and high prevalence village.

RESULTS

Three vector species were observed (23.5% Anopheles arabiensis, 31.2% Anopheles gambiae, 43.3% Anopheles coluzzii and 2.0% An. coluzzii × An. gambiae hybrids). Even at a fine scale, significant differences in species composition were detected within village pairs. Resistance to both DDT and deltamethrin was more common in An. gambiae, most markedly in the eastern part of The Gambia and partly attributable to differing frequencies of resistance mutations. The Vgsc-1014F target site mutation was strongly associated with both DDT (OR = 256.7, (95% CI 48.6-6374.3, p < 0.001) and deltamethrin survival (OR = 9.14, (95% CI 4.24-21.4, p < 0.001). A second target site mutation, Vgsc-1575Y, which co-occurs with Vgsc-1014F, and a metabolic marker of resistance, Gste2-114T, conferred additional survival benefits to both insecticides. DDT resistance occurred significantly more frequently in villages with high malaria prevalence (p = 0.025) though this did not apply to deltamethrin resistance.

CONCLUSION

Whilst causality of relationships requires further investigation, variation in vector species and insecticide resistance in The Gambia is associated with malaria endemicity; with a notably higher prevalence of infection and insecticide resistance in the east of the country. In areas with heterogeneous malaria transmission, the role of the vector should be investigated to guide malaria control interventions.

Is Dengue Vector Control Deficient in Effectiveness or Evidence?: Systematic Review and Meta-analysis

BACKGROUND

Although a vaccine could be available as early as 2016, vector control remains the primary approach used to prevent dengue, the most common and widespread arbovirus of humans worldwide. We reviewed the evidence for effectiveness of vector control methods in reducing its transmission.

METHODOLOGY/PRINCIPAL FINDINGS

Studies of any design published since 1980 were included if they evaluated method(s) targeting Aedes aegypti or Ae. albopictus for at least 3 months. Primary outcome was dengue incidence. Following Cochrane and PRISMA Group guidelines, database searches yielded 960 reports, and 41 were eligible for inclusion, with 19 providing data for meta-analysis. Study duration ranged from 5 months to 10 years. Studies evaluating multiple tools/approaches (23 records) were more common than single methods, while environmental management was the most common method (19 studies). Only 9/41 reports were randomized controlled trials (RCTs). Two out of 19 studies evaluating dengue incidence were RCTs, and neither reported any statistically significant impact. No RCTs evaluated effectiveness of insecticide space-spraying (fogging) against dengue. Based on meta-analyses, house screening significantly reduced dengue risk, OR 0.22 (95% CI 0.05-0.93, p = 0.04), as did combining community-based environmental management and water container covers, OR 0.22 (95% CI 0.15-0.32, p<0.0001). Indoor residual spraying (IRS) did not impact significantly on infection risk (OR 0.67; 95% CI 0.22-2.11; p = 0.50). Skin repellents, insecticide-treated bed nets or traps had no effect (p>0.5), but insecticide aerosols (OR 2.03; 95% CI 1.44-2.86) and mosquito coils (OR 1.44; 95% CI 1.09-1.91) were associated with higher dengue risk (p = 0.01). Although 23/41 studies examined the impact of insecticide-based tools, only 9 evaluated the insecticide susceptibility status of the target vector population during the study.

CONCLUSIONS/SIGNIFICANCE

This review and meta-analysis demonstrate the remarkable paucity of reliable evidence for the effectiveness of any dengue vector control method. Standardised studies of higher quality to evaluate and compare methods must be prioritised to optimise cost-effective dengue prevention.

Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data

Background

Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information.

Methods

We obtained weekly dengue case data from 1^st January, 2005 to 31^st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation.

Results

Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845–2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938–0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance.

Conclusion

Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.

Emerging and re-emerging infectious diseases in an urban city could expand due to increased urbanization, population density, and travel. Dengue, as a mosquito-borne viral disease, has rapidly spread from endemic areas to dengue-free regions, with social, demographic, entomological, and environmental factors affecting its transmission. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. In this study, we demonstrated that the dengue outbreaks in Guangzhou could impact outbreaks in Zhongshan, one of its neighboring cities, if suitable climate conditions are present. Such associations between dengue epidemics in two cities may also suggest the important role human movement has played in the transmission of the disease. Based on the association between dengue epidemics in Guangzhou and Zhongshan, and the association between dengue epidemics and weather conditions, we developed a reliable and robust model that predicts the occurrence of epidemics at diffrent thresholds in Zhongshan. These results could be used by local health departments in developing strategies towards dengue prevention and control, and push the public to pay more attention to social factors like human movement in disease transmission.

The Risk of Dengue Virus Transmission in Dar es Salaam, Tanzania during an Epidemic Period of 2014

Background

In 2010, 2012, 2013 and 2014 dengue outbreaks have been reported in Dar es Salaam, Tanzania. However, there is no comprehensive data on the risk of transmission of dengue in the country. The objective of this study was to assess the risk of transmission of dengue in Dar es Salaam during the 2014 epidemic.

Methodology/Principal Findings

This cross-sectional study was conducted in Dar es Salaam, Tanzania during the dengue outbreak of 2014. The study involved Ilala, Kinondoni and Temeke districts. Adult mosquitoes were collected using carbon dioxide-propane powered Mosquito Magnet Liberty Plus traps. In each household compound, water-holding containers were examined for mosquito larvae and pupae. Dengue virus infection of mosquitoes was determined using real-time reverse transcription polymerase chain reaction (qRT-PCR). Partial amplification and sequencing of dengue virus genome in infected mosquitoes was performed. A total of 1,000 adult mosquitoes were collected. Over half (59.9%) of the adult mosquitoes were collected in Kinondoni. Aedes aegypti accounted for 17.2% of the mosquitoes of which 90.6% were from Kinondoni. Of a total of 796 houses inspected, 38.3% had water-holding containers in their premises. Kinondoni had the largest proportion of water-holding containers (57.7%), followed by Temeke (31.4%) and Ilala (23.4%). The most common breeding containers for the Aedes mosquitoes were discarded plastic containers and tires. High Aedes infestation indices were observed for all districts and sites, with a house index of 18.1% in Ilala, 25.5% in Temeke and 35.3% in Kinondoni. The respective container indices were 77.4%, 65.2% and 80.2%. Of the reared larvae and pupae, 5,250 adult mosquitoes emerged, of which 61.9% were Ae. aegypti. Overall, 27 (8.18) of the 330 pools of Ae. aegypti were positive for dengue virus. On average, the overall maximum likelihood estimate (MLE) indicates pooled infection rate of 8.49 per 1,000 mosquitoes (95%CI = 5.72–12.16). There was no significant difference in pooled infection rates between the districts. Dengue viruses in the tested mosquitoes clustered into serotype 2 cosmopolitan genotype.

Conclusions/Significance

Ae. aegypti is the main vector of dengue in Dar es Salaam and breeds mainly in medium size plastic containers and tires. The Aedes house indices were high, indicating that the three districts were at high risk of dengue transmission. The 2014 dengue outbreak was caused by Dengue virus serotype 2. The high mosquito larval and pupal indices in the area require intensification of vector surveillance along with source reduction and health education.

Until 2010, little was known about Dengue in Tanzania. Since then, four outbreaks have been reported in Dar es Salaam City. This study was therefore carried out to assess the risk of transmission of dengue in Dar es Salaam during an outbreak in 2014. In this study adult mosquitoes were collected using carbon dioxide-propane powered traps. In addition, household compounds were visited and all water-holding containers examined for presence of mosquito larvae and pupae. Mosquito virus infection was determined using real-time reverse transcription polymerase chain reaction (qRT-PCR). Of the total of 1,000 adult mosquitoes collected, Aedes aegypti accounted for 17.2%. A total of 796 houses were inspected and 38.3% had water-holding containers in their premises. The most common breeding containers for the Aedes mosquitoes were discarded plastic containers and tires. High Aedes infestation indices were observed for all districts and sites, with a house and container indices ranging from 18.1–25.5% and 65.2–80.2%, respectively. The Breteaux indices were 30.6, 20.8 and 25.3 in Ilala, Kinondoni and Temeke, respectively. An overall 8.18% of mosquito pools were infected with dengue virus serotype 2. The overall maximum likelihood estimate of pooled infection rate of 8.49 per 1,000 mosquitoes was observed. This information is useful for the design of appropriate vector surveillance and control strategies in the City of Dar es Salaam.

The Spread of Dengue in an Endemic Urban Milieu--The Case of Delhi, India

BACKGROUND

Dengue is a major international public health concern, one of the most important arthropod-borne diseases. More than 3.5 billion people are at risk of dengue infection and there are an estimated 390 million dengue infections annually. This prolific increase has been connected to societal changes such as population growth and increasing urbanization generating intense agglomeration leading to proliferation of synanthropic mosquito species. Quantifying the spatio-temporal epidemiology of dengue in large cities within the context of a Geographic Information System is a first step in the identification of socio-economic risk factors.

METHODOLOGY/PRINCIPAL FINDINGS

This Project has been approved by the ethical committee of Institut Pasteur. Data has been anonymized and de-identified prior to geolocalisation and analysis. A GIS was developed for Delhi, enabling typological characterization of the urban environment. Dengue cases identified in the Delhi surveillance system from 2008 to 2010 were collated, localised and embedded within this GIS. The spatio-temporal distribution of dengue cases and extent of clustering were analyzed. Increasing distance from the forest in Delhi reduced the risk of occurrence of a dengue case. Proximity to a hospital did not increase risk of a notified dengue case. Overall, there was high heterogeneity in incidence rate within areas with the same socio-economical profiles and substantial inter-annual variability. Dengue affected the poorest areas with high density of humans, but rich areas were also found to be infected, potentially because of their central location with respect to the daily mobility network of Delhi. Dengue cases were highly clustered in space and there was a strong relationship between the time of introduction of the virus and subsequent cluster size. At a larger scale, earlier introduction predicted the total number of cases.

CONCLUSIONS/SIGNIFICANCE

DENV epidemiology within Delhi has a forest fire signature. The stochastic nature of this invasion process likely smothers any detectable socio-economic risk factors. However, the significant finding that the size of the dengue case cluster depends on the timing of its emergence emphasizes the need for early case detection and implementation of effective mosquito control. A better understanding of the role of population mobility in contributing to dengue risk could also help focus control on areas at particular risk of dengue virus importation.

Evolutionary Medicine IV. Evolution and Emergence of Novel Pathogens

This article discusses how evolutionary and ecological factors interact to affect the epidemiology of emerging infectious diseases. It further explains how the nascent field of phylodynamics constructs mathematical models, which link evolution and epidemiology, to study pathogen transmission. To illustrate the importance of considering both evolution and ecology – along with the utility of the phylodynamic approach – when studying novel pathogens, the author considers examples from HIV, influenza, and Ebola.

Peridomestic Infection as a Determining Factor of Dengue Transmission

Background

The study of endemic dengue transmission is essential for proposing alternatives to impact its burden. The traditional paradigm establishes that transmission starts around cases, but there are few studies that determine the risk.

Methods

To assess the association between the peridomestic dengue infection and the exposure to a dengue index case (IC), a cohort was carried out in two Mexican endemic communities. People cohabitating with IC or living within a 50-meter radius (exposed cohort) and subjects of areas with no ICs in a 200-meter radius (unexposed cohort) were included.

Results

Exposure was associated with DENV infection in cohabitants (PRa 3.55; 95%CI 2.37–5.31) or neighbors (PRa 1.82; 95%CI 1.29–2.58). Age, location, toilets with no direct water discharge, families with children younger than 5 and the House Index, were associated with infection. Families with older than 13 were associated with a decreased frequency. After a month since the IC fever onset, the infection incidence was not influenced by exposure to an IC or vector density; it was influenced by the local seasonal behavior of dengue and the age. Additionally, we found asymptomatic infections accounted for 60% and a greater age was a protective factor for the presence of symptoms (RR 0.98; 95%CI 0.97–0.99).

Conclusion

The evidence suggests that dengue endemic transmission in these locations is initially peridomestic, around an infected subject who may be asymptomatic due to demographic structure and endemicity, and it is influenced by other characteristics of the individual, the neighborhood and the location. Once the transmission chain has been established, dengue spreads in the community probably by the adults who, despite being the group with lower infection frequency, mostly suffer asymptomatic infections and have higher mobility. This scenario complicates the opportunity and the effectiveness of control programs and highlights the need to apply multiple measures for dengue control.

The study of dengue transmission is essential for proposing alternatives to diminish the cases and the cost of dengue treatment and control. The traditional paradigm establishes that transmission chain starts around a case, but there are few studies that determine the risk, therefore, we studied if to live around a dengue case increases the risk to get infected by Dengue virus. We interviewed and took blood samples from people cohabitating with dengue cases and neighbors in two Mexican communities, to compare we interviewed and took blood samples from subjects of areas without dengue cases in these communities. We found that people cohabitating and neighbors had more risk to get infected. Younger and older person, the workers, families with children younger than 5, houses with toilets with no direct water discharge, and areas with more mosquitoes, also had increased infection risk until one month after the fever onset of dengue case. After this month the frequency of dengue infections was only influenced by the seasonal behavior of dengue and the age of the subjects. Also, we found that 60% of infections are asymptomatic and older people have less risk to develop symptoms. This study suggests that dengue transmission in these locations is initially peridomestic, around the houses of infected subject who may be asymptomatic (without symptoms), and it is influenced by other characteristics of the individual, the neighborhood and the community. After this peridomestic transmission, dengue spreads in the community probably by adults who mostly suffer asymptomatic infections and have higher mobility, which complicates the application and affects the results of vector control programs.

Human Social Behavior and Demography Drive Patterns of Fine-Scale Dengue Transmission in Endemic Areas of Colombia

Dengue is known to transmit between humans and A. aegypti mosquitoes living in neighboring houses. Although transmission is thought to be highly heterogeneous in both space and time, little is known about the patterns and drivers of transmission in groups of houses in endemic settings. We carried out surveys of PCR positivity in children residing in 2-block patches of highly endemic cities of Colombia. We found high levels of heterogeneity in PCR positivity, varying from less than 30% in 8 of the 10 patches to 56 and 96%, with the latter patch containing 22 children simultaneously PCR positive (PCR22) for DEN2. We then used an agent-based model to assess the likely eco-epidemiological context of this observation. Our model, simulating daily dengue dynamics over a 20 year period in a single two block patch, suggests that the observed heterogeneity most likely derived from variation in the density of susceptible people. Two aspects of human adaptive behavior were critical to determining this density: external social relationships favoring viral introduction (by susceptible residents or infectious visitors) and immigration of households from non-endemic areas. External social relationships generating frequent viral introduction constituted a particularly strong constraint on susceptible densities, thereby limiting the potential for explosive outbreaks and dampening the impact of heightened vectorial capacity. Dengue transmission can be highly explosive locally, even in neighborhoods with significant immunity in the human population. Variation among neighborhoods in the density of local social networks and rural-to-urban migration is likely to produce significant fine-scale heterogeneity in dengue dynamics, constraining or amplifying the impacts of changes in mosquito populations and cross immunity between serotypes.

Characterizing Types of Human Mobility to Inform Differential and Targeted Malaria Elimination Strategies in Northeast Cambodia

Human population movements currently challenge malaria elimination in low transmission foci in the Greater Mekong Subregion. Using a mixed-methods design, combining ethnography (n = 410 interviews), malariometric data (n = 4996) and population surveys (n = 824 indigenous populations; n = 704 Khmer migrants) malaria vulnerability among different types of mobile populations was researched in the remote province of Ratanakiri, Cambodia. Different structural types of human mobility were identified, showing differential risk and vulnerability. Among local indigenous populations, access to malaria testing and treatment through the VMW-system and LLIN coverage was high but control strategies failed to account for forest farmers’ prolonged stays at forest farms/fields (61% during rainy season), increasing their exposure (p = 0.002). The Khmer migrants, with low acquired immunity, active on plantations and mines, represented a fundamentally different group not reached by LLIN-distribution campaigns since they were largely unregistered (79%) and unaware of the local VMW-system (95%) due to poor social integration. Khmer migrants therefore require control strategies including active detection, registration and immediate access to malaria prevention and control tools from which they are currently excluded. In conclusion, different types of mobility require different malaria elimination strategies. Targeting mobility without an in-depth understanding of malaria risk in each group challenges further progress towards elimination.

From within host dynamics to the epidemiology of infectious disease: Scientific overview and challenges

Since their earliest days, humans have been struggling with infectious diseases. Caused by viruses, bacteria, protozoa, or even higher organisms like worms, these diseases depend critically on numerous intricate interactions between parasites and hosts, and while we have learned much about these interactions, many details are still obscure. It is evident that the combined host-parasite dynamics constitutes a complex system that involves components and processes at multiple scales of time, space, and biological organization. At one end of this hierarchy we know of individual molecules that play crucial roles for the survival of a parasite or for the response and survival of its host. At the other end, one realizes that the spread of infectious diseases by far exceeds specific locales and, due to today's easy travel of hosts carrying a multitude of organisms, can quickly reach global proportions. The community of mathematical modelers has been addressing specific aspects of infectious diseases for a long time. Most of these efforts have focused on one or two select scales of a multi-level disease and used quite different computational approaches. This restriction to a molecular, physiological, or epidemiological level was prudent, as it has produced solid pillars of a foundation from which it might eventually be possible to launch comprehensive, multi-scale modeling efforts that make full use of the recent advances in biology and, in particular, the various high-throughput methodologies accompanying the emerging -omics revolution. This special issue contains contributions from biologists and modelers, most of whom presented and discussed their work at the workshop From within Host Dynamics to the Epidemiology of Infectious Disease, which was held at the Mathematical Biosciences Institute at Ohio State University in April 2014. These contributions highlight some of the forays into a deeper understanding of the dynamics between parasites and their hosts, and the consequences of this dynamics for the spread and treatment of infectious diseases.

Theory and data for simulating fine-scale human movement in an urban environment

Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it.

Heterogeneity in the prevalence and intensity of bovine trypanosomiasis in the districts of Amuru and Nwoya, Northern Uganda

Background

Livestock trypanosomiasis, transmitted mainly by tsetse flies of the genus Glossina is a major constraint to livestock health and productivity in the sub-Saharan Africa. Knowledge of the prevalence and intensity of trypanosomiasis is important in understanding the epidemiology of the disease. The objectives of this study were to (a) assess the prevalence and intensity of trypanosome infections in cattle, and (b) to investigate the reasons for the heterogeneity of the disease in the tsetse infested districts of Amuru and Nwoya, northern Uganda.

Methods

A cross-sectional study was conducted from September, 2011 to January, 2012. Blood samples were collected from 816 cattle following jugular vein puncture, and screened for trypanosomes by HCT and ITS-PCR. A Pearson chi-squared test and logistic regression analyses were performed to determine the association between location, age, sex, and prevalence of trypanosome infections.

Results

Out of the 816 blood samples examined, 178 (22 %) and 338 (41 %) tested positive for trypanosomiasis by HCT and ITS-PCR, respectively. Trypanosoma vivax infection accounted for 77 % of infections detected by ITS-PCR, T. congolense (16 %), T. brucei s.l (4 %) and mixed (T. vivax/ T. congolense/T.brucei) infections (3 %). The risk of trypanosome infection was significantly associated with cattle age (χ²  = 220.4, df = 3, P < 0.001). The highest proportions of infected animals were adult males (26.7 %) and the least infected were the less than one year old calves (2.0 %). In addition, the risk of trypanosome infection was significantly associated with sex (χ² = 16.64, df = 1, P < 0.001), and males had a significantly higher prevalence of infections (26.8 %) than females (14.6 %).

Conclusion

Our results indicate that the prevalence and intensity of trypanosome infections are highly heterogeneous being associated with cattle age, location and sex.

Malaria ecology along the Thailand-Myanmar border

Background

Malaria in Southeast Asia frequently clusters along international borders. For example, while most of Thailand is malaria free, the border region shared with Myanmar continues to have endemic malaria. This spatial pattern is the result of complex interactions between landscape, humans, mosquito vectors, and malaria parasites. An understanding of these complex ecological and socio-cultural interactions is important for designing and implementing malaria elimination efforts in the region. This article offers an ecological perspective on the malaria situation along the Thailand–Myanmar border.

Discussion

This border region is long (2000 km), mountainous, and the environment ranges from thick forests to growing urban settlements and wet-rice fields. It is also a biologically diverse region. All five species of malaria known to naturally infect humans are present. At least three mosquito vector species complexes, with widely varying behavioural characteristics, exist in the area. The region is also a hub for ethnic diversity, being home to over ten different ethnolinguistic groups, several of which have been engaged in conflict with the Myanmar government now for over half a century. Given the biological and ethnic diversity, as well as the complex socio-political context, malaria control and elimination in the region is challenging.

Conclusion

Despite these complexities, multipronged approaches including collaborations with multiple local organizations, quick access to diagnosis and treatment, prevention of mosquito bites, radical cure of parasites, and mass drug administration appear to be drastically decreasing Plasmodium falciparum infections. Such approaches remain crucial as the region moves toward elimination of P. falciparum and potentially Plasmodium vivax.

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra’s algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

Mobility dynamics of migrant workers and their socio-behavioral parameters related to malaria in Tier II, Artemisinin Resistance Containment Zone, Myanmar

Background

Areas with dynamic population movements are likely to be associated with higher levels of drug-resistant malaria. Myanmar Artemisinin Resistance Containment (MARC) Project has been launching since 2012. One of its components includes enhancing strategic approaches for mobile/migrant populations. We aimed to ascertain the estimated population of mobile migrant workers and their families in terms of stability in work setting in townships classified as tier II (areas with significant inflows of people from areas with credible evidence of artemisinin resistance) for Artemisinin resistance; to identify knowledge, attitudes and practices related to prevention and control of malaria and to recommend cost-effective strategies in planning for prevention and control of malaria.

Methods

A prospective cross-sectional study conducted between June to December 2013 that covered 1,899 migrant groups from 16 tier II townships of Bago Region, and Kayin and Kayah States. Trained data collectors used a pre-tested and subsequently modified questionnaire and interviewed 2,381 respondents. Data of migrant groups were analyzed and compared by category depending upon the stability of their work setting.

Results

The estimated population of the 1,899 migrant groups categorized into three on the nature of their work setting was 56,030. Bago region was the commonest reported source of origin of migrant groups as well as their transit. Malaria volunteers were mostly within the reach of category 1 migrant groups (43/66, 65.2 %). Less stable migrant groups in category 3 had limited access to malaria information (14.7 %) and malaria care providers (22.1 %), low level of awareness and use of long-lasting insecticide-treated nets (46.6 and 38.8 %). Also, they had poor knowledge on malaria prevention on confirming suspected malaria and on using artemisinin combined therapy (ACT). Within two weeks prior to the survey, only 16.5 % of respondents in all categories combined reported acute undifferentiated fever.

Discussion and Conclusions

Mobility dynamics of migrant groups was complex and increased their vulnerability to malaria. This phenomenon was accentuated in less stable areas. Even though migrant workers were familiar with rapid diagnostic tests for malaria, ACT still needed wide recognition to improve practices supportive of MARC including the use of appropriate personal protection. High mobility calls for re-designation of tier II townships to optimize ACT resistance containment.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-015-2241-0) contains supplementary material, which is available to authorized users.

Impact of human mobility on the emergence of dengue epidemics in Pakistan

The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness.

Seroprevalence of West Nile Virus specific IgG and IgM antibodies in North-Western and Western provinces of Zambia

BACKGROUND

West Nile Virus (WNV) infection has been reported worldwide, including in Africa but its existence in Zambia is unknown. Symptoms for the virus include headache, myalgia, arthralgia and rash.

OBJECTIVES

This study aimed to determine the seroprevalence of WNV and its correlates.

METHODS

A cross sectional study was conducted in North-Western and Western provinces of Zambia. Samples were subjected to IgG and IgM antibodies testing against WNV. Logistic regression analyses were conducted to determine magnitudes of association.

RESULTS

A total of 3,625 of persons participated in the survey out of which 10.3% had WNV infection. Farmers were 20% (AOR=0.80; 95% CI [0.64, 0.99]) less likely to have infection compared to students. Meanwhile participants who lived in grass roofed houses were 2.97 (AOR=2.97; 95% CI [1.81, 4.88]) times more likely to be infected than those who lived in asbestos roofed houses. IRS was associated with reduced risk of infection (AOR=0.81; 95% CI [0.69, 0.94]). Travelling to Angola was associated with the infection [AOR=1.40; 95% CI [1.09, 1.81].

CONCLUSION

Spraying houses with insecticide residual spray would minimize mosquito-man contact. Furthermore, surveillance at the border with Angola should be enhanced in order to reduce importation of the virus into the country.

Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data

Changing patterns of human aggregation are thought to drive annual and multiannual outbreaks of infectious diseases, but the paucity of data about travel behavior and population flux over time has made this idea difficult to test quantitatively. Current measures of human mobility, especially in low-income settings, are often static, relying on approximate travel times, road networks, or cross-sectional surveys. Mobile phone data provide a unique source of information about human travel, but the power of these data to describe epidemiologically relevant changes in population density remains unclear. Here we quantify seasonal travel patterns using mobile phone data from nearly 15 million anonymous subscribers in Kenya. Using a rich data source of rubella incidence, we show that patterns of population travel (fluxes) inferred from mobile phone data are predictive of disease transmission and improve significantly on standard school term time and weather covariates. Further, combining seasonal and spatial data on travel from mobile phone data allows us to characterize seasonal fluctuations in risk across Kenya and produce dynamic importation risk maps for rubella. Mobile phone data therefore offer a valuable previously unidentified source of data for measuring key drivers of seasonal epidemics.

Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes

Background

Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather.

Methodology/Principal Findings

We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution.

Conclusions/Significance

Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning.

Timing and spatial-extent of diseases such as dengue and malaria that result from transmission between humans and mosquitoes are regulated by weather in complicated ways. For Aedes aegypti mosquitoes, the primary vector of dengue, slight changes in different components of weather have important effects on population dynamics, lifespan, biting-frequency, virus incubation period and capacity to transmit the virus, thus inducing changes in transmission probability. These complicated dynamics produce a weather-disease connection that is not well-defined for different ecological settings. Understanding this connection is important to critical elements of policy development and operational control of dengue such as predicting risk, developing human-vector transmission models, and planning surveillance-intervention strategies locally and globally. The empirical profile of the weather-disease connection for dengue developed in this study provides a needed understanding of how temperature and humidity work together in regulating human-mosquito transmission. The observed likelihood of low to epidemic-level transmission was highly sensitive to local seasonal duration in limited areas of this two-dimensional weather-space. Data presented represent a resource for estimating where and when transmission-potential supports epidemics of varying magnitude. This high-resolution weather-disease profile for dengue reveals systematic relationships that are informative for mosquito-borne diseases in general and discussions of consequences of global warming.

Spatial and Temporal Characteristics of Pastoral Mobility in the Far North Region, Cameroon: Data Analysis and Modeling

Modeling the movements of humans and animals is critical to understanding the transmission of infectious diseases in complex social and ecological systems. In this paper, we focus on the movements of pastoralists in the Far North Region of Cameroon, who follow an annual transhumance by moving between rainy and dry season pastures. Describing, summarizing, and modeling the transhumance movements in the region are important steps for understanding the role these movements may play in the transmission of infectious diseases affecting humans and animals. We collected data on this transhumance system for four years using a combination of surveys and GPS mapping. An analysis on the spatial and temporal characteristics of pastoral mobility suggests four transhumance modes, each with its own properties. Modes M1 and M2 represent the type of transhumance movements where pastoralists settle in a campsite for a relatively long period of time (≥20 days) and then move around the area without specific directions within a seasonal grazing area. Modes M3 and M4 on the other hand are the situations when pastoralists stay in a campsite for a relatively short period of time (<20 days) when moving between seasonal grazing areas. These four modes are used to develop a spatial-temporal mobility (STM) model that can be used to estimate the probability of a mobile pastoralist residing at a location at any time. We compare the STM model with two reference models and the experiments suggest that the STM model can effectively capture and predict the space-time dynamics of pastoral mobility in our study area.

Models for the effects of host movement in vector-borne disease systems

Host and/or vector movement patterns have been shown to have significant effects in both empirical studies and mathematical models of vector-borne diseases. The processes of economic development and globalization seem likely to make host movement even more important in the future. This article is a brief survey of some of the approaches that have been used to study the effects of host movement in analytic mathematical models for vector-borne diseases. It describes the formulation and interpretation of various types of spatial models and describes a few of the conclusions that can be drawn from them. It is not intended to be comprehensive but rather to provide sufficient background material and references to the literature to serve as an entry point into this area of research for interested readers.

Climate Factors as Important Determinants of Dengue Incidence in Curaçao

Macro- and microclimates may have variable impact on dengue incidence in different settings. We estimated the short-term impact and delayed effects of climate variables on dengue morbidity in Curaçao. Monthly dengue incidence data from 1999 to 2009 were included to estimate the short-term influences of climate variables by employing wavelet analysis, generalized additive models (GAM) and distributed lag nonlinear models (DLNM) on rainfall, temperature and relative humidity in relation to dengue incidence. Dengue incidence showed a significant irregular 4-year multi-annual cycle associated with climate variables. Based on GAM, temperature showed a U-shape, while humidity and rainfall exhibited a dome-shaped association, suggesting that deviation from mean temperature increases and deviation from mean humidity and rainfall decreases dengue incidence, respectively. Rainfall was associated with an immediate increase in dengue incidence of 4.1% (95% CI: 2.2-8.1%) after a 10-mm increase, with a maximum increase of 6.5% (95% CI: 3.2-10.0%) after 1.5 month lag. A 1 °C decrease of mean temperature was associated with a RR of 17.4% (95% CI: 11.2-27.0%); the effect was inversed for a 1°C increase of mean temperature (RR= 0.457, 95% CI: 0.278-0.752). Climate variables are important determinants of dengue incidence and provide insight into its short-term effects. An increase in mean temperature was associated with lower dengue incidence, whereas lower temperatures were associated with higher dengue incidence.

Malaria and the mobile and migrant population in Cambodia: a population movement framework to inform strategies for malaria control and elimination

BACKGROUND

The relationships between human population movement (HPM) and health are a concern at global level. In the case of malaria, those links are crucial in relation to the spread of drug resistant parasites and to the elimination of malaria in the Greater Mekong sub-Region (GMS) and beyond. The mobile and migrant populations (MMP) who are involved in forest related activities are both at high risk of being infected with malaria and at risk of receiving late and sub-standard treatment due to poor access to health services. In Cambodia, in 2012, the National Malaria Control Programme (NMCP) identified, as a key objective, the development of a specific strategy for MMPs in order to address these challenges. A population movement framework (PMF) for malaria was developed and operationalized in order to contribute to this strategy.

METHODS

A review of the published and unpublished literature was conducted. Based on a synthesis of the results, information was presented and discussed with experienced researchers and programme managers in the Cambodian NMCP and led to the development and refinement of a PMF for malaria. The framework was "tested" for face and content validity with national experts through a workshop approach.

RESULTS

In the literature, HPM has been described using various spatial and temporal dimensions both in the context of the spread of anti-malarial drug resistance, and in the context of malaria elimination and previous classifications have categorized MMPs in Cambodia and the GMS through using a number of different criteria. Building on these previous models, the PMF was developed and then refined and populated with in-depth information relevant to Cambodia collected from social science research and field experiences in Cambodia. The framework comprises of the PMF itself, MMP activity profiles and a Malaria Risk Index which is a summation of three related indices: a vulnerability index, an exposure index and an access index which allow a qualitative ranking of malaria risk in the MMP population. Application of currently available data to the framework illustrates that the highest risk population are those highly mobile populations engaged in forest work.

CONCLUSION

This paper describes the process of defining MMPs in Cambodia, identifying the different activities and related risks to appropriately target and tailor interventions to the highest risk groups. The framework has been used to develop more targeted behaviour change and outreach interventions for MMPs in Cambodia and its utility and effectiveness will be evaluated as part of those interventions.

Geo-Located Tweets. Enhancing Mobility Maps and Capturing Cross-Border Movement

Capturing human movement patterns across political borders is difficult and this difficulty highlights the need to investigate alternative data streams. With the advent of smart phones and the ability to attach accurate coordinates to Twitter messages, users leave a geographic digital footprint of their movement when posting tweets. In this study we analyzed 10 months of geo-located tweets for Kenya and were able to capture movement of people at different temporal (daily to periodic) and spatial (local, national to international) scales. We were also able to capture both long and short distances travelled, highlighting regional connections and cross-border movement between Kenya and the surrounding countries. The findings from this study has broad implications for studying movement patterns and mapping inter/intra-region movement dynamics.

Assessing the epidemiological effect of wolbachia for dengue control

Dengue viruses cause more human morbidity and mortality than any other arthropod-borne virus. Dengue prevention relies mainly on vector control; however, the failure of traditional methods has promoted the development of novel entomological approaches. Although use of the intracellular bacterium wolbachia to control mosquito populations was proposed 50 years ago, only in the past decade has its use as a potential agent of dengue control gained substantial interest. Here, we review evidence that supports a practical approach for dengue reduction through field release of wolbachia-infected mosquitoes and discuss the additional studies that have to be done before the strategy can be validated and implemented. A crucial next step is to assess the efficacy of wolbachia in reducing dengue virus transmission. We argue that a cluster randomised trial is at this time premature because choice of wolbachia strain for release and deployment strategies are still being optimised. We therefore present a pragmatic approach to acquiring preliminary evidence of efficacy through various complementary methods including a prospective cohort study, a geographical cluster investigation, virus phylogenetic analysis, virus surveillance in mosquitoes, and vector competence assays. This multipronged approach could provide valuable intermediate evidence of efficacy to justify a future cluster randomised trial.

Spatial heterogeneity, host movement and mosquito-borne disease transmission

Mosquito-borne diseases are a global health priority disproportionately affecting low-income populations in tropical and sub-tropical countries. These pathogens live in mosquitoes and hosts that interact in spatially heterogeneous environments where hosts move between regions of varying transmission intensity. Although there is increasing interest in the implications of spatial processes for mosquito-borne disease dynamics, most of our understanding derives from models that assume spatially homogeneous transmission. Spatial variation in contact rates can influence transmission and the risk of epidemics, yet the interaction between spatial heterogeneity and movement of hosts remains relatively unexplored. Here we explore, analytically and through numerical simulations, how human mobility connects spatially heterogeneous mosquito populations, thereby influencing disease persistence (determined by the basic reproduction number R0), prevalence and their relationship. We show that, when local transmission rates are highly heterogeneous, R0 declines asymptotically as human mobility increases, but infection prevalence peaks at low to intermediate rates of movement and decreases asymptotically after this peak. Movement can reduce heterogeneity in exposure to mosquito biting. As a result, if biting intensity is high but uneven, infection prevalence increases with mobility despite reductions in R0. This increase in prevalence decreases with further increase in mobility because individuals do not spend enough time in high transmission patches, hence decreasing the number of new infections and overall prevalence. These results provide a better basis for understanding the interplay between spatial transmission heterogeneity and human mobility, and their combined influence on prevalence and R0.

Cross-border malaria: a major obstacle for malaria elimination

Movement of malaria across international borders poses a major obstacle to achieving malaria elimination in the 34 countries that have committed to this goal. In border areas, malaria prevalence is often higher than in other areas due to lower access to health services, treatment-seeking behaviour of marginalized populations that typically inhabit border areas, difficulties in deploying prevention programmes to hard-to-reach communities, often in difficult terrain, and constant movement of people across porous national boundaries. Malaria elimination in border areas will be challenging and key to addressing the challenges is strengthening of surveillance activities for rapid identification of any importation or reintroduction of malaria. This could involve taking advantage of technological advances, such as spatial decision support systems, which can be deployed to assist programme managers to carry out preventive and reactive measures, and mobile phone technology, which can be used to capture the movement of people in the border areas and likely sources of malaria importation. Additionally, joint collaboration in the prevention and control of cross-border malaria by neighbouring countries, and reinforcement of early diagnosis and prompt treatment are ways forward in addressing the problem of cross-border malaria.

Improving dengue virus capture rates in humans and vectors in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance strategy

Dengue is of public health importance in tropical and sub-tropical regions. Dengue virus (DENV) transmission dynamics was studied in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance of 93 hospitalized subjects with confirmed dengue (initiates) and associated cluster individuals (associates) with entomologic sampling. A total of 438 associates were enrolled from 208 houses with household members with a history of fever, located within a 200-m radius of an initiate case. Of 409 associates, 86 (21%) had laboratory-confirmed DENV infection. A total of 63 (1.8%) of the 3,565 mosquitoes collected were dengue polymerase chain reaction positive (PCR+). There was a significant relationship between spatial proximity to the initiate case and likelihood of detecting DENV from associate cases and Aedes mosquitoes. The viral detection rate from human hosts and mosquito vectors in this study was higher than previously observed by the study team in the same geographic area using different methodologies. We propose that the sampling strategy used in this study could support surveillance of DENV transmission and vector interactions.

Predicting unprecedented dengue outbreak using imported cases and climatic factors in Guangzhou, 2014

INTRODUCTION

Dengue is endemic in more than 100 countries, mainly in tropical and subtropical regions, and the incidence has increased 30-fold in the past 50 years. The situation of dengue in China has become more and more severe, with an unprecedented dengue outbreak hitting south China in 2014. Building a dengue early warning system is therefore urgent and necessary for timely and effective response.

METHODOLOGY AND PRINCIPAL FINDINGS

In the study we developed a time series Poisson multivariate regression model using imported dengue cases, local minimum temperature and accumulative precipitation to predict the dengue occurrence in four districts of Guangzhou, China. The time series data were decomposed into seasonal, trend and remainder components using a seasonal-trend decomposition procedure based on loess (STL). The time lag of climatic factors included in the model was chosen based on Spearman correlation analysis. Autocorrelation, seasonality and long-term trend were controlled in the model. A best model was selected and validated using Generalized Cross Validation (GCV) score and residual test. The data from March 2006 to December 2012 were used to develop the model while the data from January 2013 to September 2014 were employed to validate the model. Time series Poisson model showed that imported cases in the previous month, minimum temperature in the previous month and accumulative precipitation with three month lags could project the dengue outbreaks occurred in 2013 and 2014 after controlling the autocorrelation, seasonality and long-term trend.

CONCLUSIONS

Together with the sole transmission vector Aedes albopictus, imported cases, monthly minimum temperature and monthly accumulative precipitation may be used to develop a low-cost effective early warning system.

Clustering, climate and dengue transmission

Dengue is currently the most rapidly spreading vector-borne disease, with an increasing burden over recent decades. Currently, neither a licensed vaccine nor an effective anti-viral therapy is available, and treatment largely remains supportive. Current vector control strategies to prevent and reduce dengue transmission are neither efficient nor sustainable as long-term interventions. Increased globalization and climate change have been reported to influence dengue transmission. In this article, we reviewed the non-climatic and climatic risk factors which facilitate dengue transmission. Sustainable and effective interventions to reduce the increasing threat from dengue would require the integration of these risk factors into current and future prevention strategies, including dengue vaccination, as well as the continuous support and commitment from the political and environmental stakeholders.

WITHDRAWN: From within host dynamics to the epidemiology of infectious disease: Scientific overview and challenges

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No effect of insecticide treated curtain deployment on aedes infestation in a cluster randomized trial in a setting of low dengue transmission in Guantanamo, Cuba

Objective & Methodology

The current study evaluated the effectiveness and cost-effectiveness of Insecticide Treated Curtain (ITC) deployment for reducing dengue vector infestation levels in the Cuban context with intensive routine control activities. A cluster randomized controlled trial took place in Guantanamo city, east Cuba. Twelve neighborhoods (about 500 households each) were selected among the ones with the highest Aedes infestation levels in the previous two years, and were randomly allocated to the intervention and control arms. Long lasting ITC (PermaNet) were distributed in the intervention clusters in March 2009. Routine control activities were continued in the whole study area. In both study arms, we monitored monthly pre- and post-intervention House Index (HI, number of houses with at least 1 container with Aedes immature stages/100 houses inspected), during 12 and 18 months respectively. We evaluated the effect of ITC deployment on HI by fitting a generalized linear regression model with a negative binomial link function to these data.

Principal Findings

At distribution, the ITC coverage (% of households using ≥1 ITC) reached 98.4%, with a median of 3 ITC distributed/household. After 18 months, the coverage remained 97.4%. The local Aedes species was susceptible to deltamethrin (mosquito mortality rate of 99.7%) and the residual deltamethrin activity in the ITC was within acceptable levels (mosquito mortality rate of 73.1%) after one year of curtain use. Over the 18 month observation period after ITC distribution, the adjusted HI rate ratio, intervention versus control clusters, was 1.15 (95% CI 0.57 to 2.34). The annualized cost per household of ITC implementation was 3.8 USD, against 16.8 USD for all routine ACP activities.

Conclusion

Deployment of ITC in a setting with already intensive routine Aedes control actions does not lead to reductions in Aedes infestation levels.

Utility of mosquito surveillance data for spatial prioritization of vector control against dengue viruses in three Brazilian cities

Background

Vector control remains the primary defense against dengue fever. Its success relies on the assumption that vector density is related to disease transmission. Two operational issues include the amount by which mosquito density should be reduced to minimize transmission and the spatio-temporal allotment of resources needed to reduce mosquito density in a cost-effective manner. Recently, a novel technology, MI-Dengue, was implemented city-wide in several Brazilian cities to provide real-time mosquito surveillance data for spatial prioritization of vector control resources. We sought to understand the role of city-wide mosquito density data in predicting disease incidence in order to provide guidance for prioritization of vector control work.

Methods

We used hierarchical Bayesian regression modeling to examine the role of city-wide vector surveillance data in predicting human cases of dengue fever in space and time. We used four years of weekly surveillance data from Vitoria city, Brazil, to identify the best model structure. We tested effects of vector density, lagged case data and spatial connectivity. We investigated the generality of the best model using an additional year of data from Vitoria and two years of data from other Brazilian cities: Governador Valadares and Sete Lagoas.

Results

We found that city-wide, neighborhood-level averages of household vector density were a poor predictor of dengue-fever cases in the absence of accounting for interactions with human cases. Effects of city-wide spatial patterns were stronger than within-neighborhood or nearest-neighborhood effects. Readily available proxies of spatial relationships between human cases, such as economic status, population density or between-neighborhood roadway distance, did not explain spatial patterns in cases better than unweighted global effects.

Conclusions

For spatial prioritization of vector controls, city-wide spatial effects should be given more weight than within-neighborhood or nearest-neighborhood connections, in order to minimize city-wide cases of dengue fever. More research is needed to determine which data could best inform city-wide connectivity. Once these data become available, MI-dengue may be even more effective if vector control is spatially prioritized by considering city-wide connectivity between cases together with information on the location of mosquito density and infected mosquitos.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-015-0659-y) contains supplementary material, which is available to authorized users.

Using Geographic Information for Disease Surveillance at Mass Gatherings

Mass gatherings present the medical community with an excellent window of opportunity to study infectious diseases that can be transmitted over long distances. This is because the venue of a mass gathering usually does not change year-to-year. As a result, special attention can be given to the public health risks that are introduced by travelers from around the world into these mass gatherings. Travelers can also be infected with diseases that are endemic in the host country and transport the locally acquired infectious diseases to their home environments. Therefore, mass gatherings can be thought of as global-to-local-to-global events because of the initial convergence of global populations and the subsequent divergence of populations throughout the world. This chapter discusses three active areas of geographic research that have emerged from our understanding of disease surveillance at mass gatherings: the role of transportation and population geographies in disease surveillance; the spatial and temporal dimensions of environmental geography in the spread of disease; and the advances in GIScience that provide real-world surveillance and monitoring of disease and injuries at mass gatherings.

Geographic Medicine

This chapter uses a sub-discipline of medicine, known as geographic medicine, to describe how human movements contribute to the transmission of parasites on spatial scales that exceed the limits of its natural habitat. Traditionally, public health programs have focused on the health of populations, whereas the practice of medicine has focused on the health of individuals. It should be noted, however, that the population health management owes much to the effective delivery of clinical care. This chapter demonstrates how public health is intimately linked to patient care through human movement. Nearly a century ago, people typically did not develop a disease where it is contracted or even close to that place. Today, daily travel is a common way of life in modern metropolitan areas. Large, localized mosquito populations in areas that people visit regularly may be both reservoirs and hubs of infection, even if people only pass through those locations briefly. By examining of the role of human movement across different scales, this chapter examines how public health communities can use information on pathogen transmission to increase the effectiveness of disease prevention programs and clinical care.

Spatiotemporal clustering, climate periodicity, and social-ecological risk factors for dengue during an outbreak in Machala, Ecuador, in 2010

Background

Dengue fever, a mosquito-borne viral disease, is a rapidly emerging public health problem in Ecuador and throughout the tropics. However, we have a limited understanding of the disease transmission dynamics in these regions. Previous studies in southern coastal Ecuador have demonstrated the potential to develop a dengue early warning system (EWS) that incorporates climate and non-climate information. The objective of this study was to characterize the spatiotemporal dynamics and climatic and social-ecological risk factors associated with the largest dengue epidemic to date in Machala, Ecuador, to inform the development of a dengue EWS.

Methods

The following data from Machala were included in analyses: neighborhood-level georeferenced dengue cases, national census data, and entomological surveillance data from 2010; and time series of weekly dengue cases (aggregated to the city-level) and meteorological data from 2003 to 2012. We applied LISA and Moran’s I to analyze the spatial distribution of the 2010 dengue cases, and developed multivariate logistic regression models through a multi-model selection process to identify census variables and entomological covariates associated with the presence of dengue at the neighborhood level. Using data aggregated at the city-level, we conducted a time-series (wavelet) analysis of weekly climate and dengue incidence (2003-2012) to identify significant time periods (e.g., annual, biannual) when climate co-varied with dengue, and to describe the climate conditions associated with the 2010 outbreak.

Results

We found significant hotspots of dengue transmission near the center of Machala. The best-fit model to predict the presence of dengue included older age and female gender of the head of the household, greater access to piped water in the home, poor housing condition, and less distance to the central hospital. Wavelet analyses revealed that dengue transmission co-varied with rainfall and minimum temperature at annual and biannual cycles, and we found that anomalously high rainfall and temperatures were associated with the 2010 outbreak.

Conclusions

Our findings highlight the importance of geospatial information in dengue surveillance and the potential to develop a climate-driven spatiotemporal prediction model to inform disease prevention and control interventions. This study provides an operational methodological framework that can be applied to understand the drivers of local dengue risk.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-014-0610-4) contains supplementary material, which is available to authorized users.

Epidemiological trends of dengue disease in Mexico (2000-2011): a systematic literature search and analysis

This systematic literature review describes the epidemiology of dengue disease in Mexico (2000-2011). The annual number of uncomplicated dengue cases reported increased from 1,714 in 2000 to 15,424 in 2011 (incidence rates of 1.72 and 14.12 per 100,000 population, respectively). Peaks were observed in 2002, 2007, and 2009. Coastal states were most affected by dengue disease. The age distribution pattern showed an increasing number of cases during childhood, a peak at 10-20 years, and a gradual decline during adulthood. All four dengue virus serotypes were detected. Although national surveillance is in place, there are knowledge gaps relating to asymptomatic cases, primary/secondary infections, and seroprevalence rates of infection in all age strata. Under-reporting of the clinical spectrum of the disease is also problematic. Dengue disease remains a serious public health problem in Mexico.

Status and prospects of DNA barcoding in medically important parasites and vectors

For over 10 years, DNA barcoding has been used to identify specimens and discern species. Its potential benefits in parasitology were recognized early, but its utility and uptake remain unclear. Here we review studies using DNA barcoding in parasites and vectors affecting humans and find that the technique is accurate (accords with author identifications based on morphology or other markers) in 94-95% of cases, although aspects of DNA barcoding (vouchering, marker implicated) have often been misunderstood. In a newly compiled checklist of parasites, vectors, and hazards, barcodes are available for 43% of all 1403 species and for more than half of 429 species of greater medical importance. This is encouraging coverage that would improve with an active campaign targeting parasites and vectors.

Mapping the zoonotic niche of Ebola virus disease in Africa

Ebola virus disease (EVD) is a complex zoonosis that is highly virulent in humans. The largest recorded outbreak of EVD is ongoing in West Africa, outside of its previously reported and predicted niche. We assembled location data on all recorded zoonotic transmission to humans and Ebola virus infection in bats and primates (1976–2014). Using species distribution models, these occurrence data were paired with environmental covariates to predict a zoonotic transmission niche covering 22 countries across Central and West Africa. Vegetation, elevation, temperature, evapotranspiration, and suspected reservoir bat distributions define this relationship. At-risk areas are inhabited by 22 million people; however, the rarity of human outbreaks emphasises the very low probability of transmission to humans. Increasing population sizes and international connectivity by air since the first detection of EVD in 1976 suggest that the dynamics of human-to-human secondary transmission in contemporary outbreaks will be very different to those of the past.

DOI:http://dx.doi.org/10.7554/eLife.04395.001

Since the first outbreaks of Ebola virus disease in 1976, there have been numerous other outbreaks in humans across Africa with fatality rates ranging from 50% to 90%. Humans can become infected with the Ebola virus after direct contact with blood or bodily fluids from an infected person or animal. The virus also infects and kills other primates—such as chimpanzees or gorillas—though Old World fruit bats are suspected to be the most likely carriers of the virus in the wild.

The largest recorded outbreak of Ebola virus disease is ongoing in West Africa: more people have been infected in this current outbreak than in all previous outbreaks combined. The current outbreak is also the first to occur in West Africa—which is outside the previously known range of the Ebola virus.

Pigott et al. have now updated predictions about where in Africa wild animals may harbour the virus and where the transmission of the virus from these animals to humans is possible. As such, the map identifies the regions that are most at risk of a future Ebola outbreak. The data behind these new maps include the locations of all recorded primary cases of Ebola in human populations—the ‘index’ cases—many of which have been linked to animal sources. The data also include the locations of recorded cases of Ebola virus infections in wild bats and primates from the last forty years. The maps, which were modelled using more flexible methods than previous predictions, also include new information—collected using satellites—about environmental factors and new predictions of the range of wild fruit bats.

Pigott et al. report that the transmission of Ebola virus from animals to humans is possible in 22 countries across Central and West Africa—and that 22 million people live in the areas at risk. However, outbreaks in human populations are rare and the likelihood of a human getting the disease from an infected animal still remains very low. The updated map does not include data about how infections spread from one person to another, so the next challenge is to use existing data on human-to-human transmission to better understand the likely size and extent of current and future outbreaks. As more people live in, and travel to and from, the at-risk regions than ever before, Pigott et al. note that new outbreaks of Ebola virus disease are likely to be very different to those of the past.

DOI:http://dx.doi.org/10.7554/eLife.04395.002

Avian roosting behavior influences vector-host interactions for West Nile virus hosts

BACKGROUND

Extensive work has shown that vectors almost never feed at random. Often, a subset of individual hosts and host species are fed on much more frequently than expected from their abundance and this can amplify pathogen transmission. However, the drivers of variation in contact patterns between vectors and their hosts are not well understood, even in relatively well-studied systems such as West Nile virus (WNV).

METHODS

We compared roosting height and roost aggregation size of seven avian host species of WNV with patterns of host-seeking mosquito (Culex pipiens) abundance at communal and non-communal roost sites.

RESULTS

First, host-seeking mosquito abundance increased with height and paralleled increased mosquito feeding preferences on species roosting higher in the tree canopy. Second, there were several hundred-fold fewer mosquitoes per bird trapped at American robin (Turdus migratorius) communal roosts compared to non-communal roost sites, which could reduce transmission from and to this key amplifying host species. Third, seasonal changes in communal roost formation may partly explain observed seasonal changes in mosquito feeding patterns, including a decrease in feeding on communal roosting robins.

CONCLUSIONS

These results illustrate how variation in habitat use by hosts and vectors and social aggregation by hosts influence vector-host interactions and link the behavioral ecology of birds and the transmission of vector-borne diseases to humans.

Human exposure to early morning Anopheles funestus biting behavior and personal protection provided by long-lasting insecticidal nets

A shift towards early morning biting behavior of the major malaria vector Anopheles funestus have been observed in two villages in south Benin following distribution of long-lasting insecticidal nets (LLINs), but the impact of these changes on the personal protection efficacy of LLINs was not evaluated. Data from human and An. funestus behavioral surveys were used to measure the human exposure to An. funestus bites through previously described mathematical models. We estimated the personal protection efficacy provided by LLINs and the proportions of exposure to bite occurring indoors and/or in the early morning. Average personal protection provided by using of LLIN was high (≥80% of the total exposure to bite), but for LLIN users, a large part of remaining exposure occurred outdoors (45.1% in Tokoli-V and 68.7% in Lokohoué) and/or in the early morning (38.5% in Tokoli-V and 69.4% in Lokohoué). This study highlights the crucial role of LLIN use and the possible need to develop new vector control strategies targeting malaria vectors with outdoor and early morning biting behavior. This multidisciplinary approach that supplements entomology with social science and mathematical modeling illustrates just how important it is to assess where and when humans are actually exposed to malaria vectors before vector control program managers, policy-makers and funders conclude what entomological observations imply.

Beyond mobile populations: a critical review of the literature on malaria and population mobility and suggestions for future directions

BACKGROUND

Although population mobility is frequently cited as a barrier to malaria elimination, a comparatively small body of literature has attempted to systematically examine this issue. This article reviews the literature on malaria and mobile populations in order to critically examine the ways that malaria elimination experts perceive the risks surrounding population mobility. The article brings in perspectives from HIV/AIDS and other infectious disease control programmes working in areas of high population mobility. The article aims to move beyond the current tendency to identify mobile populations as a risk group and suggests ways to reconceptualize and respond to population mobility within malaria elimination.

METHODS

The review was commissioned by the Asia Pacific Malaria Elimination Network (APMEN). Searches were made using PubMed, ProQuest, Google and Google Scholar. The review includes English language published peer-reviewed literature and grey literature published up to November 2013.

RESULTS

The review identified three key themes in the literature: mobility, economic development and shifting land use; concerns about accessing mobile populations; and imported and border malaria. The review found that the literature treats mobile populations as a homogenous entity and is yet to develop a more accurate understanding of the true risks surrounding population mobility. Concerns about accessing mobile populations are overstated, and methods are suggested for working collaboratively with mobile populations. Finally, the review found that many concerns about mobile populations and imported malaria would be more productively framed as border health issues.

CONCLUSION

The focus on mobile populations is both excessive and insufficiently examined within the current literature. By its very nature, population mobility requires malaria elimination programmes to look beyond isolated localities and demographic groups to respond to the interconnections that mobility creates between localities and population groups. Malaria programmes will gain greater clarity by refocusing the discussion away from mobile populations as a risk group and toward mobility as a system involving interconnected localities and multiple demographic groups. Rather than focusing on mobile populations as a risk group and a barrier to elimination, malaria elimination programmes ought to develop collaborative community engagement efforts in border areas and regions of high population mobility and where imported malaria is of concern.

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru

Background

Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels.

Methodologies/Principal Findings

Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance) were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study.

Conclusions/Significance

Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots.

We carried out a comprehensive study of the long-term trends in household-level Aedes aegypti spatial distribution within a well-defined urban area endemic for dengue virus. By using a dataset consisting of 13,662 household entomological visits performed in two neighborhoods in Iquitos, Peru, we quantified the ∼3 year spatial clustering patterns of Ae. aegypti among houses and the temporal persistence of vector abundance hotspots. Our results provide strong support for the conclusion that Ae. aegypti distribution is highly focal and that hotspots of high vector abundance at the level of small groups of houses are common, but temporally unstable. Results from our study have implications for understanding the spatio-temporal patterns of Ae. aegypti abundance and for the design of surveillance and control activities that are based on household-level entomological data.