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1.  Models of the impact of dengue vaccines: a review of current research and potential approaches 
Vaccine  2011;29(35):5860-5868.
Vaccination reduces transmission of pathogens directly, by preventing individual infections, and indirectly, by reducing the probability of contact between infected individuals and susceptible ones. The potential combined impact of future dengue vaccines can be estimated using mathematical models of transmission. However, there is considerable uncertainty in the structure of models that accurately represent dengue transmission dynamics. Here, we review models that could be used to assess the impact of future dengue immunization programmes. We also review approaches that have been used to validate and parameterize models. A key parameter of all approaches is the basic reproduction number, R0, which can be used to determine the critical vaccination fraction to eliminate transmission. We review several methods that have been used to estimate this quantity. Finally, we discuss the characteristics of dengue vaccines that must be estimated to accurately assess their potential impact on dengue virus transmission.
doi:10.1016/j.vaccine.2011.06.042
PMCID: PMC4327892  PMID: 21699949
dengue; vaccine; theoretical model; review
2.  Incubation periods of acute respiratory viral infections: a systematic review 
The Lancet. Infectious diseases  2009;9(5):291-300.
Knowledge of the incubation period is essential in the investigation and control of infectious disease, but statements of incubation period are often poorly referenced, inconsistent, or based on limited data. In a systematic review of the literature on nine respiratory viral infections of public-health importance, we identified 436 articles with statements of incubation period and 38 with data for pooled analysis. We fitted a log-normal distribution to pooled data and found the median incubation period to be 5·6 days (95% CI 4·8–6·3) for adenovirus, 3·2 days (95% CI 2·8–3·7) for human coronavirus, 4·0 days (95% CI 3·6–4·4) for severe acute respiratory syndrome coronavirus, 1·4 days (95% CI 1·3–1·5) for influenza A, 0·6 days (95% CI 0·5–0·6) for influenza B, 12·5 days (95% CI 11·8–13·3) for measles, 2·6 days (95% CI 2·1–3·1) for parainfluenza, 4·4 days (95% CI 3·9–4·9) for respiratory syncytial virus, and 1·9 days (95% CI 1·4–2·4) for rhinovirus. When using the incubation period, it is important to consider its full distribution: the right tail for quarantine policy, the central regions for likely times and sources of infection, and the full distribution for models used in pandemic planning. Our estimates combine published data to give the detail necessary for these and other applications.
doi:10.1016/S1473-3099(09)70069-6
PMCID: PMC4327893  PMID: 19393959
3.  Estimating Potential Incidence of MERS-CoV Associated with Hajj Pilgrims to Saudi Arabia, 2014 
PLoS Currents  2014;6:ecurrents.outbreaks.c5c9c9abd636164a9b6fd4dbda974369.
Between March and June 2014 the Kingdom of Saudi Arabia (KSA) had a large outbreak of MERS-CoV, renewing fears of a major outbreak during the Hajj this October. Using KSA Ministry of Health data, the MERS-CoV Scenario and Modeling Working Group forecast incidence under three scenarios. In the expected incidence scenario, we estimate 6.2 (95% Prediction Interval [PI]: 1–17) pilgrims will develop MERS-CoV symptoms during the Hajj, and 4.0 (95% PI: 0–12) foreign pilgrims will be infected but return home before developing symptoms. In the most pessimistic scenario, 47.6 (95% PI: 32–66) cases will develop symptoms during the Hajj, and 29.0 (95% PI: 17–43) will be infected but return home asymptomatic. Large numbers of MERS-CoV cases are unlikely to occur during the 2014 Hajj even under pessimistic assumptions, but careful monitoring is still needed to detect possible mass infection events and minimize introductions into other countries.  
doi:10.1371/currents.outbreaks.c5c9c9abd636164a9b6fd4dbda974369
PMCID: PMC4323406
infectious disease; MERS-coronavirus
4.  Potential opportunities and perils of imperfect dengue vaccines 
Vaccine  2013;32(4):514-520.
Dengue vaccine development efforts have focused on the development of tetravalent vaccines. However, a recent Phase IIb trial of a tetravalent vaccine indicates a protective effect against only 3 of the 4 serotypes. While vaccines effective against a subset of serotypes may reduce morbidity and mortality, particular profiles could result in an increased number of cases due to immune enhancement and other peculiarities of dengue epidemiology. Here, we use a compartmental transmission model to assess the impact of partially effective vaccines in a hyperendemic Thai population. Crucially, we evaluate the effects that certain serotype heterogeneities may have in the presence of mass-vaccination campaigns.
In the majority of scenarios explored, partially effective vaccines lead to 50% or greater reductions in the number of cases. This is true even of vaccines that we would not expect to proceed to licensure due to poor or incomplete immune responses. Our results show that a partially effective vaccine can have significant impacts on serotype distribution and mean age of cases.
doi:10.1016/j.vaccine.2013.11.020
PMCID: PMC4142437  PMID: 24269318
5.  Characterizing the Temporal Dynamics of Human Papillomavirus DNA Detectability Using Short-Interval Sampling 
Background
Variable detection of human papillomavirus (HPV) DNA can result in misclassification of infection status, but the extent of misclassification has not been quantitatively evaluated.
Methods
In 2005–2007, 33 women aged 22–53 self-collected vaginal swabs twice per week for 16 consecutive weeks. Each of the 955 swabs collected was tested for 37 HPV types/subtypes. Assuming that a woman’s underlying infection status did not change over the short study period, biases in prevalence estimates obtained from single versus multiple swabs were calculated. Using event history analysis methods, time to recurrent gain and loss of at least one HPV type was determined, separately. Baseline any- and high risk-HPV prevalence was 60.6% and 24.2%, respectively. Cumulative any- and high risk-HPV prevalence over the 16-week period was 84.8% and 60.6%, separately.
Results
Overall, there were 319 events of detection and 313 events of loss of detection. Median times to a recurrent detection and loss of detection was 11 and 7 days, respectively. Neither vaginal sex nor condom use during follow-up was associated with recurrent viral detection or loss of detection. Assuming the cumulative 16-week prevalence reflects the true prevalence of infection, the baseline any-HPV prevalence under-estimated infection status by 24.2%, with a bootstrapped mean of 20.2% (95% confidence interval [CI]: 8.9%, 29.6%).
Conclusions
These findings suggest that a substantial proportion of HPV-infected women are misclassified as being un-infected when using a single-time DNA measurement.
Impact
Short-term variation in detectable HPV DNA needs to be considered while interpreting the natural history of infections using single samples collected at long intervals.
doi:10.1158/1055-9965.EPI-13-0666
PMCID: PMC3947138  PMID: 24130223
Epidemiology; Human papillomavirus; Interval sampling; Misclassification bias; Prevalence
6.  Menstrual Cycle and Detectable Human Papillomavirus in Reproductive-age Women: A Time Series Study 
The Journal of Infectious Diseases  2013;208(9):1404-1415.
Background. Current evidence on the relationship between human papillomavirus (HPV) DNA detection and menstrual cycle has been inconsistent.
Methods. We included 21 nonoral contraceptive pill (non-OCP) users who self-collected vaginal samples twice per week for 16 weeks. We explored whether variable detection of HPV DNA exhibited cyclic or other structured temporal patterns. We also evaluated relationships between serial HPV prevalence, sexual behavior, and suspected bacterial vaginosis (BV) as defined by Nugent Gram stain score ≥7.
Results. During follow-up, any-type HPV prevalence varied between 61.1% and 85.0%. Although not statistically significant, we observed a maximum autocorrelation in serial HPV prevalence lagging 14 days (correlation coefficient [ρ], −0.24). Any-type HPV detection had a periodic behavior, generally repeating every 28.0 days (bootstrapped interquartile range, 22.4–28.0) and peaking around the ovulation time (adjusted odds ratio, 1.96; 95% confidence interval [CI], 1.06–3.62) as compared to menstruation. We also showed that an increase in any-type HPV prevalence preceded the beginning of a menstrual cycle by 9–12 days. There was no evidence of relationships between HPV prevalence and sexual activity or Nugent score.
Conclusions. Serially detected any-type HPV DNA showed a periodic behavior and was likely to peak in the periovulatory phase among non-OCP users.
doi:10.1093/infdis/jit337
PMCID: PMC3789568  PMID: 23885113
Auto-correlation; Bacterial Vaginosis; Human Papillomavirus; Menstrual Cycle; Nugent Score; Periodicity; Spectral Analysis; Time Series Analysis
8.  The Spatial Dynamics of Dengue Virus in Kamphaeng Phet, Thailand 
Background
Dengue is endemic to the rural province of Kamphaeng Phet, Northern Thailand. A decade of prospective cohort studies has provided important insights into the dengue viruses and their generated disease. However, as elsewhere, spatial dynamics of the pathogen remain poorly understood. In particular, the spatial scale of transmission and the scale of clustering are poorly characterized. This information is critical for effective deployment of spatially targeted interventions and for understanding the mechanisms that drive the dispersal of the virus.
Methodology/Principal Findings
We geocoded the home locations of 4,768 confirmed dengue cases admitted to the main hospital in Kamphaeng Phet province between 1994 and 2008. We used the phi clustering statistic to characterize short-term spatial dependence between cases. Further, to see if clustering of cases led to similar temporal patterns of disease across villages, we calculated the correlation in the long-term epidemic curves between communities. We found that cases were 2.9 times (95% confidence interval 2.7–3.2) more likely to live in the same village and be infected within the same month than expected given the underlying spatial and temporal distribution of cases. This fell to 1.4 times (1.2–1.7) for individuals living in villages 1 km apart. Significant clustering was observed up to 5 km. We found a steadily decreasing trend in the correlation in epidemics curves by distance: communities separated by up to 5 km had a mean correlation of 0.28 falling to 0.16 for communities separated between 20 km and 25 km. A potential explanation for these patterns is a role for human movement in spreading the pathogen between communities. Gravity style models, which attempt to capture population movement, outperformed competing models in describing the observed correlations.
Conclusions
There exists significant short-term clustering of cases within individual villages. Effective spatially and temporally targeted interventions deployed within villages may target ongoing transmission and reduce infection risk.
Author Summary
Transmission of dengue virus has long been studied in Kamphaeng Phet, Northern Thailand, but how cases are related in time and space is still unclear, as is the role of human movement in generating these patterns. Because of these knowledge gaps, public health officials cannot make educated decisions on how to target vector control interventions and mechanisms of virus dispersal are not known. We mapped the homes of dengue cases admitted to the main hospital in the province capital from 1994–2008 and quantified the spatial correlation between them. We found an almost three times greater chance that cases from the same month came from the same village than expected, given the overall distribution of cases. Some clustering was also observed between cases in neighboring villages with the overall epidemics experienced by neighboring communities also more correlated than epidemics in villages farther apart. The short-term clustering observed within individual villages implies that effective spatially targeted interventions deployed within villages may reduce infection risk. As the distance between neighboring communities exceeds the typical flight range of the dengue vector, these findings also suggest a potential role for human movement in driving the wider spread of the virus.
doi:10.1371/journal.pntd.0003138
PMCID: PMC4161352  PMID: 25211127
9.  Breaking the symmetry: Immune enhancement increases persistence of dengue viruses in the presence of asymmetric transmission rates 
Journal of theoretical biology  2013;332:203-210.
The dengue viruses exist as four antigenically distinct serotypes. These four serotypes co-circulate and interact with each other through multiple immune-mediated mechanisms. Though the majority of previous efforts to understand the transmission dynamics of dengue have assumed identical characteristics for these four serotypes, empirical data suggests that they differ from one another in important ways. Here, we examine dynamics and persistence in models that do not assume symmetry between the dengue viruses. We find that for serotype transmission rates that are only slightly asymmetric, increased transmissibility of secondary infections through immune enhancement increases the persistence of all dengue viruses in opposition to findings in symmetric models. We identify an optimal magnitude of immune enhancement that maximizes the probability of persistence of all four serotypes. In contrast to other pathogen systems where heterogeneity between serotypes in transmissibility facilitates competitive exclusion (Bremmermann and Thieme, 1989), here we find that in the presence of Antibody Dependent Enhancement (ADE) heterogeneity can increase the persistence of multiple serotypes of dengue.
doi:10.1016/j.jtbi.2013.04.036
PMCID: PMC3782297  PMID: 23665358
Dengue; Antibody dependent enhancement; Serotypical asymmetry; Dengue vaccine
10.  Social contacts and the locations in which they occur as risk factors for influenza infection 
The interaction of human social behaviour and transmission is an intriguing aspect of the life cycle of respiratory viral infections. Although age-specific mixing patterns are often assumed to be the key drivers of the age-specific heterogeneity in transmission, the association between social contacts and biologically confirmed infection has not previously been tested at the individual level. We administered a questionnaire to participants in a longitudinal cohort survey of influenza in which infection was defined by longitudinal paired serology. Using a variety of statistical approaches, we found overwhelming support for the inclusion of individual age in addition to contact variables when explaining odds of infection: the best model not including age explained only 15.7% of the deviance, whereas the best model with age explained 23.6%. However, within age groups, we did observe an association between contacts, locations and infection: median numbers of contacts (or locations) reported by those infected were higher than those from the uninfected group in every age group other than the youngest. Further, we found some support for the retention of location and contact variables in addition to age in our regression models, with excess odds of infection of approximately 10% per additional 10 contacts or one location. These results suggest that, although the relationship between age and incidence of respiratory infection at the level of the individual is not driven by self-reported social contacts, risk within an age group may be.
doi:10.1098/rspb.2014.0709
PMCID: PMC4100506  PMID: 25009062
pandemic; influenza; contact patterns
11.  Variability in Dengue Titer Estimates from Plaque Reduction Neutralization Tests Poses a Challenge to Epidemiological Studies and Vaccine Development 
Background
Accurate determination of neutralization antibody titers supports epidemiological studies of dengue virus transmission and vaccine trials. Neutralization titers measured using the plaque reduction neutralization test (PRNT) are believed to provide a key measure of immunity to dengue viruses, however, the assay's variability is poorly understood, making it difficult to interpret the significance of any assay reading. In addition there is limited standardization of the neutralization evaluation point or statistical model used to estimate titers across laboratories, with little understanding of the optimum approach.
Methodology/Principal Findings
We used repeated assays on the same two pools of serum using five different viruses (2,319 assays) to characterize the variability in the technique under identical experimental conditions. We also assessed the performance of multiple statistical models to interpolate continuous values of neutralization titer from discrete measurements from serial dilutions. We found that the variance in plaque reductions for individual dilutions was 0.016, equivalent to a 95% confidence interval of 0.45–0.95 for an observed plaque reduction of 0.7. We identified PRNT75 as the optimum evaluation point with a variance of 0.025 (log10 scale), indicating a titer reading of 1∶500 had 95% confidence intervals of 1∶240–1∶1000 (2.70±0.31 on a log10 scale). The choice of statistical model was not important for the calculation of relative titers, however, cloglog regression out-performed alternatives where absolute titers are of interest. Finally, we estimated that only 0.7% of assays would falsely detect a four-fold difference in titers between acute and convalescent sera where no true difference exists.
Conclusions
Estimating and reporting assay uncertainty will aid the interpretation of individual titers. Laboratories should perform a small number of repeat assays to generate their own variability estimates. These could be used to calculate confidence intervals for all reported titers and allow benchmarking of assay performance.
Author Summary
Plaque Reduction Neutralization Tests (PRNTs) remain the most popular approach to characterize an individual's ability to neutralize dengue viruses and are widely used in both epidemiological studies and vaccine trials. However, the underlying variability in the assay is poorly understood, hindering the interpretation of PRNT titer estimates. Further, there is little standardization of its use across laboratories limiting our ability to compare results across settings. Here we used many repeated experiments on the same serum under identical laboratory conditions to estimate the variance in titer measurements. We also identified both the optimum PRNT evaluation point and statistical model to calculate titers. By providing an estimate of the variability in the assay, laboratories will be able to provide a confidence bound on individual PRNT readings. In addition by providing recommended statistical approaches that could be used across laboratories, our findings will help the standardization of the assay across settings.
doi:10.1371/journal.pntd.0002952
PMCID: PMC4072537  PMID: 24967885
12.  The Contribution of Social Behaviour to the Transmission of Influenza A in a Human Population 
PLoS Pathogens  2014;10(6):e1004206.
Variability in the risk of transmission for respiratory pathogens can result from several factors, including the intrinsic properties of the pathogen, the immune state of the host and the host's behaviour. It has been proposed that self-reported social mixing patterns can explain the behavioural component of this variability, with simulated intervention studies based on these data used routinely to inform public health policy. However, in the absence of robust studies with biological endpoints for individuals, it is unclear how age and social behaviour contribute to infection risk. To examine how the structure and nature of social contacts influenced infection risk over the course of a single epidemic, we designed a flexible disease modelling framework: the population was divided into a series of increasingly detailed age and social contact classes, with the transmissibility of each age-contact class determined by the average contacts of that class. Fitting the models to serologically confirmed infection data from the 2009 Hong Kong influenza A/H1N1p pandemic, we found that an individual's risk of infection was influenced strongly by the average reported social mixing behaviour of their age group, rather than by their personal reported contacts. We also identified the resolution of social mixing that shaped transmission: epidemic dynamics were driven by intense contacts between children, a post-childhood drop in risky contacts and a subsequent rise in contacts for individuals aged 35–50. Our results demonstrate that self-reported social contact surveys can account for age-associated heterogeneity in the transmission of a respiratory pathogen in humans, and show robustly how these individual-level behaviours manifest themselves through assortative age groups. Our results suggest it is possible to profile the social structure of different populations and to use these aggregated data to predict their inherent transmission potential.
Author Summary
For infections such as influenza, there are several aspects to the transmission process, including the properties of the pathogen itself, the host immune system and host behaviour. Although it has been proposed that self-reported social mixing patterns can be used to explain the behavioural component of infection – and mathematical modelling studies based on reported social contacts are used routinely to inform health policy – it is not clear how these contacts contribute to individual- and group-level infection risk. By analysing the relationship between social contacts and infection patterns during the 2009 Hong Kong influenza pandemic, we show that infection risk was strongly influenced by the average reported social mixing behaviour of an individual's age group, rather than by their personal reported contacts. We also demonstrate how social contact surveys can be combined with mathematical models to create useful tools with which to study respiratory infections in humans. This should make it possible to predict how the impact of interventions will vary from one population to the next based on their contacts and, potentially, to explain differences in infection attack rates between groups with different mixing behaviours.
doi:10.1371/journal.ppat.1004206
PMCID: PMC4072802  PMID: 24968312
13.  Social mixing patterns in rural and urban areas of southern China 
A dense population, global connectivity and frequent human–animal interaction give southern China an important role in the spread and emergence of infectious disease. However, patterns of person-to-person contact relevant to the spread of directly transmitted infections such as influenza remain poorly quantified in the region. We conducted a household-based survey of travel and contact patterns among urban and rural populations of Guangdong, China. We measured the character and distance from home of social encounters made by 1821 individuals. Most individuals reported 5–10 h of contact with around 10 individuals each day; however, both distributions have long tails. The distribution of distance from home at which contacts were made is similar: most were within a kilometre of the participant's home, while some occurred further than 500 km away. Compared with younger individuals, older individuals made fewer contacts which tended to be closer to home. There was strong assortativity in age-based contact rates. We found no difference between the total number or duration of contacts between urban and rural participants, but urban participants tended to make contacts closer to home. These results can improve mathematical models of infectious disease emergence, spread and control in southern China and throughout the region.
doi:10.1098/rspb.2014.0268
PMCID: PMC4024290  PMID: 24789897
influenza; mathematical modelling; social mixing; contact diary; travel; infectious disease transmission
14.  Hospital Outbreak of Middle East Respiratory Syndrome Coronavirus 
The New England journal of medicine  2013;369(5):407-416.
BACKGROUND
In September 2012, the World Health Organization reported the first cases of pneumonia caused by the novel Middle East respiratory syndrome coronavirus (MERS-CoV). We describe a cluster of health care–acquired MERS-CoV infections.
METHODS
Medical records were reviewed for clinical and demographic information and determination of potential contacts and exposures. Case patients and contacts were interviewed. The incubation period and serial interval (the time between the successive onset of symptoms in a chain of transmission) were estimated. Viral RNA was sequenced.
RESULTS
Between April 1 and May 23, 2013, a total of 23 cases of MERS-CoV infection were reported in the eastern province of Saudi Arabia. Symptoms included fever in 20 patients (87%), cough in 20 (87%), shortness of breath in 11 (48%), and gastrointestinal symptoms in 8 (35%); 20 patients (87%) presented with abnormal chest radiographs. As of June 12, a total of 15 patients (65%) had died, 6 (26%) had recovered, and 2 (9%) remained hospitalized. The median incubation period was 5.2 days (95% confidence interval [CI], 1.9 to 14.7), and the serial interval was 7.6 days (95% CI, 2.5 to 23.1). A total of 21 of the 23 cases were acquired by person-to-person transmission in hemodialysis units, intensive care units, or in-patient units in three different health care facilities. Sequencing data from four isolates revealed a single monophyletic clade. Among 217 household contacts and more than 200 health care worker contacts whom we identified, MERS-CoV infection developed in 5 family members (3 with laboratory-confirmed cases) and in 2 health care workers (both with laboratory-confirmed cases).
CONCLUSIONS
Person-to-person transmission of MERS-CoV can occur in health care settings and may be associated with considerable morbidity. Surveillance and infection-control measures are critical to a global public health response.
doi:10.1056/NEJMoa1306742
PMCID: PMC4029105  PMID: 23782161
15.  The incubation period of cholera: A systematic review 
The Journal of infection  2012;66(5):432-438.
Summary
Objectives
Recent large cholera outbreaks highlight the need for improved understanding of the pathogenesis and epidemiology of cholera. The incubation period of cholera has important implications for clinical and public health decision-making, yet statements of the incubation period of cholera are often imprecise. Here we characterize the distribution of cholera’s incubation period.
Methods
We conducted a systematic review of the literature for statements of the incubation period of cholera and data that might aid in its estimation. We extracted individual-level data, parametrically estimated the distribution of toxigenic cholera’s incubation period, and evaluated evidence for differences between strains.
Results
The incubation period did not differ by a clinically significant margin between strains (except O1 El Tor Ogawa). We estimate the median incubation period of toxigenic cholera to be 1.4 days (95% CI, 1.3–1.6). Five percent of cholera cases will develop symptoms by 0.5 days (95% CI 0.4–0.5), and 95% by 4.4 days (95% CI 3.9–5.0) after infection.
Conclusions
We recommend that cholera investigations use a recall period of at least five days to capture relevant exposures; significantly longer than recent risk factor studies from the Haitian epidemic. This characterization of cholera’s incubation period can help improve clinical and public health practice and advance epidemiologic research.
doi:10.1016/j.jinf.2012.11.013
PMCID: PMC3677557  PMID: 23201968
Cholera; Incubation period; Vibrio cholerae
16.  The ALERT Algorithm: How to Simply Define a Period of Elevated Disease Incidence 
doi:10.5210/ojphi.v6i1.5177
PMCID: PMC4050857
influenza; outbreak detection; public health practice; surveillance
17.  Recasting the theory of mosquito-borne pathogen transmission dynamics and control 
Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of the world. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald's formula for R0 and its entomological derivative, vectorial capacity, are now used to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross–Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context for mosquito blood feeding, the movement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control.
doi:10.1093/trstmh/tru026
PMCID: PMC3952634  PMID: 24591453
Dengue; Filariasis; Malaria; Mosquito-borne pathogen transmission; Vector control; West Nile virus
18.  The Role of Viral Introductions in Sustaining Community-Based HIV Epidemics in Rural Uganda: Evidence from Spatial Clustering, Phylogenetics, and Egocentric Transmission Models 
PLoS Medicine  2014;11(3):e1001610.
Using different approaches to investigate HIV transmission patterns, Justin Lessler and colleagues find that extra-community HIV introductions are frequent and likely play a role in sustaining the epidemic in the Rakai community.
Please see later in the article for the Editors' Summary
Background
It is often assumed that local sexual networks play a dominant role in HIV spread in sub-Saharan Africa. The aim of this study was to determine the extent to which continued HIV transmission in rural communities—home to two-thirds of the African population—is driven by intra-community sexual networks versus viral introductions from outside of communities.
Methods and Findings
We analyzed the spatial dynamics of HIV transmission in rural Rakai District, Uganda, using data from a cohort of 14,594 individuals within 46 communities. We applied spatial clustering statistics, viral phylogenetics, and probabilistic transmission models to quantify the relative contribution of viral introductions into communities versus community- and household-based transmission to HIV incidence. Individuals living in households with HIV-incident (n = 189) or HIV-prevalent (n = 1,597) persons were 3.2 (95% CI: 2.7–3.7) times more likely to be HIV infected themselves compared to the population in general, but spatial clustering outside of households was relatively weak and was confined to distances <500 m. Phylogenetic analyses of gag and env genes suggest that chains of transmission frequently cross community boundaries. A total of 95 phylogenetic clusters were identified, of which 44% (42/95) were two individuals sharing a household. Among the remaining clusters, 72% (38/53) crossed community boundaries. Using the locations of self-reported sexual partners, we estimate that 39% (95% CI: 34%–42%) of new viral transmissions occur within stable household partnerships, and that among those infected by extra-household sexual partners, 62% (95% CI: 55%–70%) are infected by sexual partners from outside their community. These results rely on the representativeness of the sample and the quality of self-reported partnership data and may not reflect HIV transmission patterns outside of Rakai.
Conclusions
Our findings suggest that HIV introductions into communities are common and account for a significant proportion of new HIV infections acquired outside of households in rural Uganda, though the extent to which this is true elsewhere in Africa remains unknown. Our results also suggest that HIV prevention efforts should be implemented at spatial scales broader than the community and should target key populations likely responsible for introductions into communities.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
About 35 million people (25 million of whom live in sub-Saharan Africa) are currently infected with HIV, the virus that causes AIDS, and about 2.3 million people become newly infected every year. HIV destroys immune system cells, leaving infected individuals susceptible to other infections. HIV infection can be controlled by taking antiretroviral drugs (antiretroviral therapy, or ART) daily throughout life. Although originally available only to people living in wealthy countries, recent political efforts mean that 9.7 million people in low- and middle-income countries now have access to ART. However, ART does not cure HIV infection, so prevention of viral transmission remains extremely important. Because HIV is usually transmitted through unprotected sex with an infected partner, individuals can reduce their risk of infection by abstaining from sex, by having one or a few partners, and by using condoms. Male circumcision also reduces HIV transmission. In addition to reducing illness and death among HIV-positive people, ART also reduces HIV transmission.
Why Was This Study Done?
Effective HIV control requires an understanding of how HIV spreads through sexual networks. These networks include sexual partnerships between individuals in households, between community members in different households, and between individuals from different communities. Local sexual networks (household and intra-community sexual partnerships) are sometimes assumed to be the dominant driving force in HIV spread in sub-Saharan Africa, but are viral introductions from sexual partnerships with individuals outside the community also important? This question needs answering because the effectiveness of interventions such as ART as prevention partly depends on how many new infections in an intervention area are attributable to infection from partners residing in that area and how many are attributable to infection from partners living elsewhere. Here, the researchers use three analytical methods—spatial clustering statistics, viral phylogenetics, and egocentric transmission modeling—to ask whether HIV transmission in rural Uganda is driven predominantly by intra-community sexual networks. Spatial clustering analysis uses the geographical coordinates of households to measure the tendency of HIV-infected people to cluster spatially at scales consistent with community transmission. Viral phylogenetic analysis examines the genetic relatedness of viruses; if transmission is through local networks, viruses in newly infected individuals should more closely resemble viruses in other community members than those in people outside the community. Egocentric transmission modelling uses information on the locations of recent sexual partners to estimate the proportions of new transmissions from household, intra-community, and extra-community partners.
What Did the Researchers Do and Find?
The researchers applied their three analytical methods to data collected from 14,594 individuals living in 46 communities (governmental administrative units) in Rakai District, Uganda. Spatial clustering analysis indicated that individuals who lived in households with individuals with incident HIV (newly diagnosed) or prevalent HIV (previously diagnosed) were 3.2 times more likely than the general population to be HIV-positive themselves. Spatial clustering outside households was relatively weak, however, and was confined to distances of less than half a kilometer. Viral phylogenetic analysis indicated that 44% of phylogenetic clusters (viruses with related genetic sequences found in more than one individual) were within households, but that 40% of clusters crossed community borders. Finally, analysis of the locations of self-reported sexual partners indicated that 39% of new viral transmissions occurred within stable household partnerships, but that among people newly infected by extra-household partners, nearly two-thirds were infected by partners from outside their community.
What Do These Findings Mean?
The results of all three analyses suggest that HIV introductions into communities are frequent and are likely to play an important role in sustaining HIV transmission in the Rakai District. Specifically, within this rural HIV-endemic region (a region where HIV infection is always present), viral introductions combined with intra-household transmission account for the majority of new infections, although community-based sexual networks also play a critical role in HIV transmission. These findings may not be generalizable to the broader Ugandan population or to other regions of Africa, and their accuracy is likely to be limited by the use of self-reported sexual partner data. Nevertheless, these findings indicate that the dynamics of HIV transmission in rural Uganda (and probably elsewhere) are complex. Consequently, to halt the spread of HIV, prevention efforts will need to be implemented at spatial scales broader than individual communities, and key populations that are likely to introduce HIV into communities will need to be targeted.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001610.
Information is available from the US National Institute of Allergy and Infectious Diseases on HIV infection and AIDS
NAM/aidsmap provides basic information about HIV/AIDS, and summaries of recent research findings on HIV care and treatment
Information is available from Avert, an international AIDS charity, on many aspects of HIV/AIDS, including information on HIV and AIDS in Uganda and on HIV prevention strategies (in English and Spanish)
The UNAIDS Report on the Global AIDS Epidemic 2013 provides up-to-date information about the AIDS epidemic and efforts to halt it
The Center for AIDS Prevention Studies (University of California, San Francisco) has a fact sheet about sexual networks and HIV prevention
Wikipedia provides information on spatial clustering analysis (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
A PLOS Computational Biology Topic Page (a review article that is a published copy of record of a dynamic version of the article as found in Wikipedia) about viral phylodynamics is available
Personal stories about living with HIV/AIDS are available through Avert, NAM/aidsmap, and Healthtalkonline
doi:10.1371/journal.pmed.1001610
PMCID: PMC3942316  PMID: 24595023
19.  Interior-Point Methods for Estimating Seasonal Parameters in Discrete-Time Infectious Disease Models 
PLoS ONE  2013;8(10):e74208.
Infectious diseases remain a significant health concern around the world. Mathematical modeling of these diseases can help us understand their dynamics and develop more effective control strategies. In this work, we show the capabilities of interior-point methods and nonlinear programming (NLP) formulations to efficiently estimate parameters in multiple discrete-time disease models using measles case count data from three cities. These models include multiplicative measurement noise and incorporate seasonality into multiple model parameters. Our results show that nearly identical patterns are estimated even when assuming seasonality in different model parameters, and that these patterns show strong correlation to school term holidays across very different social settings and holiday schedules. We show that interior-point methods provide a fast and flexible approach to parameterizing models that can be an alternative to more computationally intensive methods.
doi:10.1371/journal.pone.0074208
PMCID: PMC3805536  PMID: 24167542
20.  Incubation periods of viral gastroenteritis: a systematic review 
BMC Infectious Diseases  2013;13:446.
Background
Accurate knowledge of incubation period is important to investigate and to control infectious diseases and their transmission, however statements of incubation period in the literature are often uncited, inconsistent, and/or not evidence based.
Methods
In a systematic review of the literature on five enteric viruses of public health importance, we found 256 articles with incubation period estimates, including 33 with data for pooled analysis.
Results
We fit a log-normal distribution to pooled data and found the median incubation period to be 4.5 days (95% CI 3.9-5.2 days) for astrovirus, 1.2 days (95% CI 1.1-1.2 days) for norovirus genogroups I and II, 1.7 days (95% CI 1.5-1.8 days) for sapovirus, and 2.0 days (95% CI 1.4-2.4 days) for rotavirus.
Conclusions
Our estimates combine published data and provide sufficient quantitative detail to allow for these estimates to be used in a wide range of clinical and modeling applications. This can translate into improved prevention and control efforts in settings with transmission or the risk of transmission.
doi:10.1186/1471-2334-13-446
PMCID: PMC3849296  PMID: 24066865
Incubation period; Norovirus; Rotavirus; Caliciviruses; Astrovirus; Systematic review
21.  Interactions between serotypes of dengue highlight epidemiological impact of cross-immunity 
Dengue, a mosquito-borne virus of humans, infects over 50 million people annually. Infection with any of the four dengue serotypes induces protective immunity to that serotype, but does not confer long-term protection against infection by other serotypes. The immunological interactions between serotypes are of central importance in understanding epidemiological dynamics and anticipating the impact of dengue vaccines. We analysed a 38-year time series with 12 197 serotyped dengue infections from a hospital in Bangkok, Thailand. Using novel mechanistic models to represent different hypothesized immune interactions between serotypes, we found strong evidence that infection with dengue provides substantial short-term cross-protection against other serotypes (approx. 1–3 years). This is the first quantitative evidence that short-term cross-protection exists since human experimental infection studies performed in the 1950s. These findings will impact strategies for designing dengue vaccine studies, future multi-strain modelling efforts, and our understanding of evolutionary pressures in multi-strain disease systems.
doi:10.1098/rsif.2013.0414
PMCID: PMC3730691  PMID: 23825116
dengue; infectious disease modelling; cross-protection; time-series models
22.  Disease Persistence in Epidemiological Models: The Interplay between Vaccination and Migration 
Mathematical Biosciences  2012;239(1):91-96.
We consider the interplay of vaccination and migration rates on disease persistence in epidemiological systems. We show that short-term and long-term migration can inhibit disease persistence. As a result, we show how migration changes how vaccination rates should be chosen to maintain herd immunity. In a system of coupled SIR models, we analyze how disease eradication depends explicitly on vaccine distribution and migration connectivity. The analysis suggests potentially novel vaccination policies that underscore the importance of optimal placement of finite resources.
doi:10.1016/j.mbs.2012.05.003
PMCID: PMC3391321  PMID: 22652034
epidemics; migration; vaccination; herd immunity
23.  Location-specific patterns of exposure to recent pre-pandemic strains of influenza A in southern China 
Nature communications  2011;2:423.
Variation in influenza incidence between locations is commonly observed on large spatial scales. It is unclear whether such variation occurs on smaller spatial scales and whether it is the result of heterogeneities in population demographics or more subtle differences in population structure and connectivity. Here we show significant differences in immunity to influenza A viruses among communities in China not explained by differences in population demographics. We randomly selected households from 5 randomly selected locations near Guangzhou, China to answer a questionnaire and provide a blood sample for serological testing against 5 recently circulating influenza viruses. We find a significant reduction in the frequency of detectable neutralization titers with increasing age, leveling off in older age groups. There are significant differences between locations in age, employment status, vaccination history, household size and housing conditions. However, after adjustment, significant variations in the frequency of detectable neutralization titers persists between locations. These results suggest there are characteristics of communities that drive influenza transmission dynamics apart from individual and household level risk factors, and that such factors have effects independent of strain.
doi:10.1038/ncomms1432
PMCID: PMC3757505  PMID: 21829185
epidemiology; influenza; dynamics
25.  Rapid 13C Urea Breath Test to Identify Helicobacter pylori Infection in Emergency Department Patients with Upper Abdominal Pain 
Introduction: In emergency department (ED) patients with upper abdominal pain, management includes ruling out serious diseases and providing symptomatic relief. One of the major causes of upper abdominal pain is an ulcer caused by Helicobacter pylori (H. pylori), which can be treated and cured with antibiotics. We sought to estimate the prevalence of H. pylori infection in symptomatic patients using a convenience sample at a single urban academic ED and demonstrate the feasibility of ED-based testing.
Methods: We prospectively enrolled patients with a chief complaint of pain or discomfort in the upper abdomen for 1 year from February 2011 until February 2012 at a single academic urban ED. Enrolled subjects were tested for H. pylori using a rapid point of care 13C Urea Breath Test (UBT) [Exalenz Bioscience]. We compared patient characteristics between those who tested positive versus negative for the disease.
Results: A total of 205 patients with upper abdominal pain were tested over 12 months, and 24% (95% confidence interval: 19% to 30%) tested positive for H. pylori. Black subjects were more likely to test positive than white subjects (28% v. 6%, P < 0.001). Other factors, such as age and sex, were not different between the 2 groups.
Conclusion: In our ED, H. pylori infection was present in 1 in 4 patients with epigastric pain, and testing with a UBT was feasible. Further study is needed to determine the risk factors associated with infection, the prevalence of H. pylori in other EDs, the effect of the test on ED length of stay and the costeffectiveness of an ED-based test-and-treat strategy.
doi:10.5811/westjem.2012.12.15173
PMCID: PMC3656711  PMID: 23687549

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