Eric S. Halsey

House-to-house human movement drives dengue virus transmission

Dengue is a mosquito-borne disease of growing global health importance. Prevention efforts focus on mosquito control, with limited success. New insights into the spatiotemporal drivers of dengue dynamics are needed to design improved disease-prevention strategies. Given the restricted range of movement of the primary mosquito vector, Aedes aegypti, local human movements may be an important driver of dengue virus (DENV) amplification and spread. Using contact-site cluster investigations in a case-control design, we demonstrate that, at an individual level, risk for human infection is defined by visits to places where contact with infected mosquitoes is likely, independent of distance from the home. Our data indicate that house-to-house human movements underlie spatial patterns of DENV incidence, causing marked heterogeneity in transmission rates. At a collective level, transmission appears to be shaped by social connections because routine movements among the same places, such as the homes of family and friends, are often similar for the infected individual and their contacts. Thus, routine, house-to-house human movements do play a key role in spread of this vector-borne pathogen at fine spatial scales. This finding has important implications for dengue prevention, challenging the appropriateness of current approaches to vector control. We argue that reexamination of existing paradigms regarding the spatiotemporal dynamics of DENV and other vector-borne pathogens, especially the importance of human movement, will lead to improvements in disease prevention.

Using GPS technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environment.

Empiric quantification of human mobility patterns is paramount for better urban planning, understanding social network structure and responding to infectious disease threats, especially in light of rapid growth in urbanization and globalization. This need is of particular relevance for developing countries, since they host the majority of the global urban population and are disproportionally affected by the burden of disease. We used Global Positioning System (GPS) data-loggers to track the fine-scale (within city) mobility patterns of 582 residents from two neighborhoods from the city of Iquitos, Peru. We used ∼2.3 million GPS data-points to quantify age-specific mobility parameters and dynamic co-location networks among all tracked individuals. Geographic space significantly affected human mobility, giving rise to highly local mobility kernels. Most (∼80%) movements occurred within 1 km of an individual’s home. Potential hourly contacts among individuals were highly irregular and temporally unstructured. Only up to 38% of the tracked participants showed a regular and predictable mobility routine, a sharp contrast to the situation in the developed world. As a case study, we quantified the impact of spatially and temporally unstructured routines on the dynamics of transmission of an influenza-like pathogen within an Iquitos neighborhood. Temporally unstructured daily routines (e.g., not dominated by a single location, such as a workplace, where an individual repeatedly spent significant amount of time) increased an epidemic’s final size and effective reproduction number by 20% in comparison to scenarios modeling temporally structured contacts. Our findings provide a mechanistic description of the basic rules that shape human mobility within a resource-poor urban center, and contribute to the understanding of the role of fine-scale patterns of individual movement and co-location in infectious disease dynamics. More generally, this study emphasizes the need for careful consideration of human social interactions when designing infectious disease mitigation strategies, particularly within resource-poor urban environments.

Reduced Risk of Disease During Postsecondary Dengue Virus Infections

BACKGROUND Antibodies induced by infection with any 1 of 4 dengue virus (DENV) serotypes (DENV-1-4) may influence the clinical outcome of subsequent heterologous infections. To quantify potential cross-protective effects, we estimated disease risk as a function of DENV infection, using data from longitudinal studies performed from September 2006 through February 2011 in Iquitos, Peru, during periods of DENV-3 and DENV-4 transmission. METHODS DENV infections before and during the study period were determined by analysis of serial serum samples with virus neutralization tests. Third and fourth infections were classified as postsecondary infections. Dengue fever cases were detected by door-to-door surveillance for acute febrile illness. RESULTS Among susceptible participants, 39% (420/1077) and 53% (1595/2997) seroconverted to DENV-3 and DENV-4, respectively. Disease was detected in 7% of DENV-3 infections and 10% of DENV-4 infections. Disease during postsecondary infections was reduced by 93% for DENV-3 and 64% for DENV-4, compared with primary and secondary infections. Despite lower disease rates, postsecondary infections constituted a significant proportion of apparent infections (14% [for DENV-3 infections], 45% [for DENV-4 infections]). CONCLUSIONS Preexisting heterotypic antibodies markedly reduced but did not eliminate the risk of disease in this study population. These results improve understanding of how preinfection history can be associated with dengue outcomes and DENV transmission dynamics.

Time-varying, serotype-specific force of infection of dengue virus

Significance Using mathematical models to extend knowledge of pathogen transmission and recommend optimized control efforts is dependent on the accuracy of model parameters. The rate at which susceptible individuals become infected [the force of infection (FoI)] is one of the most important parameters, but due to data constraints it is often incorrectly assumed to be constant over time. Using a bespoke method for a 12-y longitudinal dataset of serotype-specific dengue virus (DENV) infections, we estimated time-varying, serotype-specific FoIs for all four DENV serotypes. The FoI varied markedly in time, which implies that DENV transmission dynamics are complex and are best summarized using time-dependent transmission parameters. Our results provide more accurate measures of virus transmission dynamics and a basis for improving selection of control and disease prevention strategies. Infectious disease models play a key role in public health planning. These models rely on accurate estimates of key transmission parameters such as the force of infection (FoI), which is the per-capita risk of a susceptible person being infected. The FoI captures the fundamental dynamics of transmission and is crucial for gauging control efforts, such as identifying vaccination targets. Dengue virus (DENV) is a mosquito-borne, multiserotype pathogen that currently infects ∼390 million people a year. Existing estimates of the DENV FoI are inaccurate because they rely on the unrealistic assumption that risk is constant over time. Dengue models are thus unreliable for designing vaccine deployment strategies. Here, we present to our knowledge the first time-varying (daily), serotype-specific estimates of DENV FoIs using a spline-based fitting procedure designed to examine a 12-y, longitudinal DENV serological dataset from Iquitos, Peru (11,703 individuals, 38,416 samples, and 22,301 serotype-specific DENV infections from 1999 to 2010). The yearly DENV FoI varied markedly across time and serotypes (0–0.33), as did daily basic reproductive numbers (0.49–4.72). During specific time periods, the FoI fluctuations correlated across serotypes, indicating that different DENV serotypes shared common transmission drivers. The marked variation in transmission intensity that we detected indicates that intervention targets based on one-time estimates of the FoI could underestimate the level of effort needed to prevent disease. Our description of dengue virus transmission dynamics is unprecedented in detail, providing a basis for understanding the persistence of this rapidly emerging pathogen and improving disease prevention programs.

Effect of the Ebola-virus-disease epidemic on malaria case management in Guinea, 2014: a cross-sectional survey of health facilities

Summary Background The ongoing west Africa Ebola-virus-disease epidemic has disrupted the entire health-care system in affected countries. Because of the overlap of symptoms of Ebola virus disease and malaria, the care delivery of malaria is particularly sensitive to the indirect effects of the current Ebola-virus-disease epidemic. We therefore characterise malaria case management in the context of the Ebola-virus-disease epidemic and document the effect of the Ebola-virus-disease epidemic on malaria case management. Methods We did a cross-sectional survey of public health facilities in Guinea in December, 2014. We selected the four prefectures most affected by Ebola virus disease and selected four randomly from prefectures without any reported cases of the disease. 60 health facilities were sampled in Ebola-affected and 60 in Ebola-unaffected prefectures. Study teams abstracted malaria case management indicators from registers for January to November for 2013 and 2014 and interviewed health-care workers. Nationwide weekly surveillance data for suspect malaria cases reported between 2011 and 2014 were analysed independently. Data for malaria indicators in 2014 were compared with previous years. Findings We noted substantial reductions in all-cause outpatient visits (by 23 103 [11%] of 214 899), cases of fever (by 20249 [15%] of 131 330), and patients treated with oral (by 22 655 [24%] of 94 785) and injectable (by 5219 [30%] of 17 684) antimalarial drugs in surveyed health facilities. In Ebola-affected prefectures, 73 of 98 interviewed community health workers were operational (74%, 95% CI 65–83) and 35 of 73 were actively treating malaria cases (48%, 36–60) compared with 106 of 112 (95%, 89–98) and 102 of 106 (96%, 91–99), respectively, in Ebola-unaffected prefectures. Nationwide, the Ebola-virus-disease epidemic was estimated to have resulted in 74 000 (71 000–77 000) fewer malaria cases seen at health facilities in 2014. Interpretation The reduction in the delivery of malaria care because of the Ebola-virus-disease epidemic threatens malaria control in Guinea. Untreated and inappropriately treated malaria cases lead to excess malaria mortality and more fever cases in the community, impeding the Ebola-virus-disease response. Funding Global Fund to Fight AIDS, Tuberculosis and Malaria, and Presidents Malaria Initiative.

A Three-Component Biomarker Panel for Prediction of Dengue Hemorrhagic Fever

Dengue virus infections are a major cause of morbidity in tropical countries. Early detection of dengue hemorrhagic fever (DHF) may help identify individuals that would benefit from intensive therapy. Predictive modeling was performed using 11 laboratory values of 51 individuals (38 DF and 13 DHF) obtained on initial presentation using logistic regression. We produced a robust model with an area under the curve of 0.9615 that retained IL-10 levels, platelets, and lymphocytes as the major predictive features. A classification and regression tree was developed on these features that were 86% accurate on cross-validation. The IL-10 levels and platelet counts were also identified as the most informative features associated with DHF using a Random Forest classifier. In the presence of polymerase chain reaction-proven acute dengue infections, we suggest a complete blood count and rapid measurement of IL-10 can assist in the triage of potential DHF cases for close follow-up or clinical intervention improving clinical outcome.

Iquitos virus: a novel reassortant Orthobunyavirus associated with human illness in Peru.

Oropouche (ORO) virus, a member of the Simbu serogroup, is one of the few human pathogens in the Orthobunyavirus genus in the family Bunyaviridae. Genetic analyses of ORO-like strains from Iquitos, Peru, identified a novel reassortant containing the S and L segments of ORO virus and the M segment of a novel Simbu serogroup virus. This new pathogen, which we named Iquitos (IQT) virus, was first isolated during 1999 from a febrile patient in Iquitos, an Amazonian city in Peru. Subsequently, the virus was identified as the cause of outbreaks of “Oropouche fever” during 2005 and 2006 in Iquitos. In addition to the identification of 17 isolates of IQT virus between 1999 and 2006, surveys for neutralizing antibody among Iquitos residents revealed prevalence rates of 14.9% for ORO virus and 15.4% for IQT virus. Limited studies indicate that prior infection with ORO virus does not seem to protect against disease caused with the IQT virus infection. Identification of a new Orthobunyavirus human pathogen in the Amazon region of Peru highlights the need for strengthening surveillance activities and laboratory capabilities, and investigating the emergence of new pathogens in tropical regions of South America.

Correlation of Serotype-Specific Dengue Virus Infection with Clinical Manifestations

Background Disease caused by the dengue virus (DENV) is a significant cause of morbidity throughout the world. Although prior research has focused on the association of specific DENV serotypes (DENV-1, DENV-2, DENV-3, and DENV-4) with the development of severe outcomes such as dengue hemorrhagic fever and dengue shock syndrome, relatively little work has correlated other clinical manifestations with a particular DENV serotype. The goal of this study was to estimate and compare the prevalence of non-hemorrhagic clinical manifestations of DENV infection by serotype. Methodology and Principal Findings Between the years 2005–2010, individuals with febrile disease from Peru, Bolivia, Ecuador, and Paraguay were enrolled in an outpatient passive surveillance study. Detailed information regarding clinical signs and symptoms, as well as demographic information, was collected. DENV infection was confirmed in patient sera with polyclonal antibodies in a culture-based immunofluorescence assay, and the infecting serotype was determined by serotype-specific monoclonal antibodies. Differences in the prevalence of individual and organ-system manifestations were compared across DENV serotypes. One thousand seven hundred and sixteen individuals were identified as being infected with DENV-1 (39.8%), DENV-2 (4.3%), DENV-3 (41.5%), or DENV-4 (14.4%). When all four DENV serotypes were compared with each other, individuals infected with DENV-3 had a higher prevalence of musculoskeletal and gastrointestinal manifestations, and individuals infected with DENV-4 had a higher prevalence of respiratory and cutaneous manifestations. Conclusions/Significance Specific clinical manifestations, as well as groups of clinical manifestations, are often overrepresented by an individual DENV serotype.

Spatial and Temporal Characteristics of the 2009 A/H1N1 Influenza Pandemic in Peru

Background Highly refined surveillance data on the 2009 A/H1N1 influenza pandemic are crucial to quantify the spatial and temporal characteristics of the pandemic. There is little information about the spatial-temporal dynamics of pandemic influenza in South America. Here we provide a quantitative description of the age-specific morbidity pandemic patterns across administrative areas of Peru. Methods We used daily cases of influenza-like-illness, tests for A/H1N1 influenza virus infections, and laboratory-confirmed A/H1N1 influenza cases reported to the epidemiological surveillance system of Perus Ministry of Health from May 1 to December 31, 2009. We analyzed the geographic spread of the pandemic waves and their association with the winter school vacation period, demographic factors, and absolute humidity. We also estimated the reproduction number and quantified the association between the winter school vacation period and the age distribution of cases. Results The national pandemic curve revealed a bimodal winter pandemic wave, with the first peak limited to school age children in the Lima metropolitan area, and the second peak more geographically widespread. The reproduction number was estimated at 1.6–2.2 for the Lima metropolitan area and 1.3–1.5 in the rest of Peru. We found a significant association between the timing of the school vacation period and changes in the age distribution of cases, while earlier pandemic onset was correlated with large population size. By contrast there was no association between pandemic dynamics and absolute humidity. Conclusions Our results indicate substantial spatial variation in pandemic patterns across Peru, with two pandemic waves of varying timing and impact by age and region. Moreover, the Peru data suggest a hierarchical transmission pattern of pandemic influenza A/H1N1 driven by large population centers. The higher reproduction number of the first pandemic wave could be explained by high contact rates among school-age children, the age group most affected during this early wave.

Evaluation of dengue NS1 antigen rapid tests and ELISA kits using clinical samples.

Background Early diagnosis of dengue virus (DENV) infection can improve clinical outcomes by ensuring close follow-up, initiating appropriate supportive therapies and raising awareness to the potential of hemorrhage or shock. Non-structural glycoprotein-1 (NS1) has proven to be a useful biomarker for early diagnosis of dengue. A number of rapid diagnostic tests (RDTs) and enzyme-linked immunosorbent assays (ELISAs) targeting NS1 antigen (Ag) are now commercially available. Here we evaluated these tests using a well-characterized panel of clinical samples to determine their effectiveness for early diagnosis. Methodology/Principal Findings Retrospective samples from South America were used to evaluate the following tests: (i) “Dengue NS1 Ag STRIP” and (ii) “Platelia Dengue NS1 Ag ELISA” (Bio-Rad, France), (iii) “Dengue NS1 Detect Rapid Test (1st Generation)” and (iv) “DENV Detect NS1 ELISA” (InBios International, United States), (v) “Panbio Dengue Early Rapid (1st generation)” (vi) “Panbio Dengue Early ELISA (2nd generation)” and (vii) “SD Bioline Dengue NS1 Ag Rapid Test” (Alere, United States). Overall, the sensitivity of the RDTs ranged from 71.9%–79.1% while the sensitivity of the ELISAs varied between 85.6–95.9%, using virus isolation as the reference method. Most tests had lower sensitivity for DENV-4 relative to the other three serotypes, were less sensitive in detecting secondary infections, and appeared to be most sensitive on Day 3–4 post symptom onset. The specificity of all evaluated tests ranged from 95%–100%. Conclusions ELISAs had greater overall sensitivity than RDTs. In conjunction with other parameters, the performance data can help determine which dengue diagnostics should be used during the first few days of illness, when the patients are most likely to present to a clinic seeking care.