Force Of Infection Research Articles

Estimating dengue transmission intensity from serological data: A comparative analysis using mixture and catalytic models.

Dengue virus (DENV) infection is a global health concern of increasing magnitude. To target intervention strategies, accurate estimates of the force of infection (FOI) are necessary. Catalytic models have been widely used to estimate DENV FOI and rely on a binary classification of serostatus as seropositive or seronegative, according to pre-defined antibody thresholds. Previous work has demonstrated the use of thresholds can cause serostatus misclassification and biased estimates. In contrast, mixture models do not rely on thresholds and use the full distribution of antibody titres. To date, there has been limited application of mixture models to estimate DENV FOI. We compare the application of mixture models and time-constant and time-varying catalytic models to simulated data and to serological data collected in Vietnam from 2004 to 2009 (N ≥ 2178) and Indonesia in 2014 (N = 3194). The simulation study showed larger mean FOI estimate bias from the time-constant and time-varying catalytic models (-0.007 (95% Confidence Interval (CI): -0.069, 0.029) and -0.006 (95% CI -0.095, 0.043)) than from the mixture model (0.001 (95% CI -0.036, 0.065)). Coverage of the true FOI was > 95% for estimates from both the time-varying catalytic and mixture model, however the latter had reduced uncertainty. When applied to real data from Vietnam, the mixture model frequently produced higher FOI and seroprevalence estimates than the catalytic models. Our results suggest mixture models represent valid, potentially less biased, alternatives to catalytic models, which could be particularly useful when estimating FOI from data with largely overlapping antibody titre distributions.

Time-dependent force of infection and effective reproduction ratio in an age-structure dengue transmission model in Bandung City, Indonesia.

Dengue virus infection is a leading health problem in many endemic countries, including Indonesia, characterized by high morbidity and wide spread. It is known that the risk factors that influence the transmission intensity vary among different age groups, which can have implications for dengue control strategies. A time-dependent four − age structure model of dengue transmission was constructed in this study. A vaccination scenario as control strategy was also applied to one of the age groups. Daily incidence data of dengue cases from Santo Borromeus Hospital, Bandung, Indonesia, from 2014 to 2016 was used to estimate the infection rate. We used two indicators to identify the changes in dengue transmission intensity for this period in each age group: the annual force of infection (FoI) and the effective reproduction ratio based on a time-dependent transmission rate. The results showed that the yearly FoI of children (age 0–4 years) increased significantly from 2014 to 2015, at 10.08%. Overall, the highest FoI before and after vaccination occurred in youngsters (age 5–14 years), with a FoI of about 6% per year. In addition, based on the daily effective reproduction ratio, it was found that vaccination of youngsters could reduce the number of dengue cases in Bandung city faster than vaccination of children.

Spatiotemporal variations in exposure: Chagas disease in Colombia as a case study

Age-stratified serosurvey data are often used to understand spatiotemporal trends in disease incidence and exposure through estimating the Force-of-Infection (FoI). Typically, median or mean FoI estimates are used as the response variable in predictive models, often overlooking the uncertainty in estimated FoI values when fitting models and evaluating their predictive ability. To assess how this uncertainty impact predictions, we compared three approaches with three levels of uncertainty integration. We propose a performance indicator to assess how predictions reflect initial uncertainty.In Colombia, 76 serosurveys (1980–2014) conducted at municipality level provided age-stratified Chagas disease prevalence data. The yearly FoI was estimated at the serosurvey level using a time-varying catalytic model. Environmental, demographic and entomological predictors were used to fit and predict the FoI at municipality level from 1980 to 2010 across Colombia.A stratified bootstrap method was used to fit the models without temporal autocorrelation at the serosurvey level. The predictive ability of each model was evaluated to select the best-fit models within urban, rural and (Amerindian) indigenous settings. Model averaging, with the 10 best-fit models identified, was used to generate predictions.Our analysis shows a risk of overconfidence in model predictions when median estimates of FoI alone are used to fit and evaluate models, failing to account for uncertainty in FoI estimates. Our proposed methodology fully propagates uncertainty in the estimated FoI onto the generated predictions, providing realistic assessments of both central tendency and current uncertainty surrounding exposure to Chagas disease.

1013. Predicting RSV Efficacy for MK-1654 in Temperate and Tropical Climates using MBMA and Clinical Trial Simulation to Account for Seasonal Differences in RSV Force-of-Infection

Abstract Background MK-1654 is a respiratory syncytial virus (RSV) F glycoprotein neutralizing monoclonal antibody under development to prevent RSV infection in infants. A model-based meta-analysis (MBMA) describing the relationship between RSV serum neutralizing activity (SNA) and clinically relevant endpoints (e.g. incidence rates) in humans, including lower respiratory tract infection (LRI) in infants, was presented previously. This model accounted for variable exposure to RSV over the course of the season through a force-of-infection (FOI) function modulating the overall risk of RSV infection over time. The objective of the current work was to determine whether variations in regional seasonality would impact the efficacy of a clinical trial evaluating MK-1654. Methods A FOI function to describe the degree of RSV exposure as a function of time was created by fitting epidemiological data to a Gaussian function added to a constant baseline value. Clinical trial simulations were conducted using the MBMA to predict seasonal incidence rates (IR) of RSV medically attended lower-respiratory tract infection (MALRI) and efficacies for a range of MK-1654 doses in both temperate and tropical regions. Results Epidemiological data was well captured by the FOI function. Clinical trial simulations indicated that seasonal IRs of RSV were sensitive to differences in the FOI represented by temperate and tropical regions; however, there was no substantial impact on efficacies across MK-1654 dose levels. Consistent with predictions for a temperate climate, MK-1654, when administered at the start of the RSV season in a region with a tropical climate, was also predicted to maintain high efficacy ( > 75%) for the prevention of RSV MALRI for 150 days. Conclusion Simulations indicated that while FOI is a substantial driver of overall RSV incidence rates, MK-1654 efficacy in a late-stage clinical trial is likely to be high, regardless of regional variations in RSV. Disclosures Nele Plock, PhD, Certara (Employee, Shareholder)Merck & Co., Inc. (Independent Contractor) Jos Lommerse, PhD, Certara (Employee, Shareholder)Merck & Co., Inc. (Independent Contractor) Brian M. Maas, PharmD, Merck & Co., Inc. (Employee, Shareholder) Jingxian Chen, PhD, Merck & Co., Inc. (Employee, Shareholder) Francesco Bellanti, PhD, Certara (Employee, Shareholder)Merck & Co., Inc. (Independent Contractor) Li Qin, PhD, Certara (Employee, Shareholder)Merck & Co., Inc. (Independent Contractor) Han Witjes, PhD, Certara (Employee, Shareholder)Merck & Co., Inc. (Independent Contractor) Philippe Pierrillas, PhD, Certara (Employee, Shareholder)Merck & Co., Inc. (Independent Contractor) Radha Railkar, PhD, Merck & Co., Inc. (Employee, Shareholder) Antonios O. Aliprantis, MD, PhD, Merck & Co., Inc. (Employee, Shareholder) Kalpit A. Vora, PhD, Merck & Co., Inc. (Employee, Shareholder) Wei Gao, PhD, Merck & Co., Inc. (Employee, Shareholder) Luzelena Caro, PhD, Merck & Co., Inc. (Employee, Shareholder) S. Y. Amy Cheung, PhD, Certara (Employee, Shareholder) Jeffrey R. Sachs, PhD, Merck & Co., Inc. (Employee, Shareholder)

The current burden of Japanese encephalitis and the estimated impacts of vaccination: Combining estimates of the spatial distribution and transmission intensity of a zoonotic pathogen.

Japanese encephalitis virus (JEV) is a major cause of neurological disability in Asia and causes thousands of severe encephalitis cases and deaths each year. Although Japanese encephalitis (JE) is a WHO reportable disease, cases and deaths are significantly underreported and the true burden of the disease is not well understood in most endemic countries. Here, we first conducted a spatial analysis of the risk factors associated with JE to identify the areas suitable for sustained JEV transmission and the size of the population living in at-risk areas. We then estimated the force of infection (FOI) for JE-endemic countries from age-specific incidence data. Estimates of the susceptible population size and the current FOI were then used to estimate the JE burden from 2010 to 2019, as well as the impact of vaccination. Overall, 1,543.1 million (range: 1,292.6-2,019.9 million) people were estimated to live in areas suitable for endemic JEV transmission, which represents only 37.7% (range: 31.6-53.5%) of the over four billion people living in countries with endemic JEV transmission. Based on the baseline number of people at risk of infection, there were an estimated 56,847 (95% CI: 18,003-184,525) JE cases and 20,642 (95% CI: 2,252-77,204) deaths in 2019. Estimated incidence declined from 81,258 (95% CI: 25,437-273,640) cases and 29,520 (95% CI: 3,334-112,498) deaths in 2010, largely due to increases in vaccination coverage which have prevented an estimated 314,793 (95% CI: 94,566-1,049,645) cases and 114,946 (95% CI: 11,421-431,224) deaths over the past decade. India had the largest estimated JE burden in 2019, followed by Bangladesh and China. From 2010-2019, we estimate that vaccination had the largest absolute impact in China, with 204,734 (95% CI: 74,419-664,871) cases and 74,893 (95% CI: 8,989-286,239) deaths prevented, while Taiwan (91.2%) and Malaysia (80.1%) had the largest percent reductions in JE burden due to vaccination. Our estimates of the size of at-risk populations and current JE incidence highlight countries where increasing vaccination coverage could have the largest impact on reducing their JE burden.

Estimating the annual dengue force of infection from the age of reporting primary infections across urban centres in endemic countries

BackgroundStratifying dengue risk within endemic countries is crucial for allocating limited control interventions. Current methods of monitoring dengue transmission intensity rely on potentially inaccurate incidence estimates. We investigated whether incidence or alternate metrics obtained from standard, or laboratory, surveillance operations represent accurate surrogate indicators of the burden of dengue and can be used to monitor the force of infection (FOI) across urban centres.MethodsAmong those who reported and resided in 13 cities across the Philippines, we collected epidemiological data from all dengue case reports between 2014 and 2017 (N 80,043) and additional laboratory data from a cross-section of sampled case reports (N 11,906) between 2014 and 2018. At the city level, we estimated the aggregated annual FOI from age-accumulated IgG among the non-dengue reporting population using catalytic modelling. We compared city-aggregated FOI estimates to aggregated incidence and the mean age of clinically and laboratory diagnosed dengue cases using Pearson’s Correlation coefficient and generated predicted FOI estimates using regression modelling.ResultsWe observed spatial heterogeneity in the dengue average annual FOI across sampled cities, ranging from 0.054 [0.036–0.081] to 0.249 [0.223–0.279]. Compared to FOI estimates, the mean age of primary dengue infections had the strongest association (ρ −0.848, p value<0.001) followed by the mean age of those reporting with warning signs (ρ −0.642, p value 0.018). Using regression modelling, we estimated the predicted annual dengue FOI across urban centres from the age of those reporting with primary infections and revealed prominent spatio-temporal heterogeneity in transmission intensity.ConclusionsWe show the mean age of those reporting with their first dengue infection or those reporting with warning signs of dengue represent superior indicators of the dengue FOI compared to crude incidence across urban centres. Our work provides a framework for national dengue surveillance to routinely monitor transmission and target control interventions to populations most in need.

Quantitative evaluation of the infection dynamics of bovine brucellosis in Tanzania

Brucellosis is endemic in Tanzania. A cross-sectional study was conducted at 17 cattle farms in agro-pastoral areas in Tanzania to identify risk factors associated with the within-farm prevalence of bovine brucellosis and to quantitatively assess the infection dynamics through disease modelling. Cattle blood sampling and interviews with farmers using a structured questionnaire were conducted. A total of 673 serum samples were screened using the Rose-Bengal plate test (RBPT), and sero-positivity of RBPT-positive samples was confirmed using a competitive enzyme-linked immunosorbent assay. Zero-inflated binomial regression was performed for univariable and multivariable risk factor analyses of within-farm prevalence. Several susceptible-infectious (SI) models were compared based on deviance information criteria, and age-dependent force of infection (FOI) was measured using age-specific prevalence data for the 10 infection-positive farms. Using the diagnoses of cows on the 17 farms, the basic reproduction number, R0, was also calculated. The farm-level prevalence and animal-level adjusted prevalence were 58.8 % (10/17, 95 % confidence interval: 33.5–80.6 %) and 7.0 % (28/673, 95 % credible interval: 5.7–8.4 %), respectively. The risk factor for high within-farm prevalence was introduction of cattle from other herds. A mathematical model with constant FOI showed the annual probability of infection as 1.4 % (95 % credible interval: 1.0 %–2.0 %). The R0 was 1.07. The constant FOI could have been due to the predominant mode of infection being transmission of Brucella from contaminated aborted materials during grazing. Direct purchase of infected cattle could facilitate efficient transmission between susceptible animals through abortion.

The epidemiology of Mayaro virus in the Americas: A systematic review and key parameter estimates for outbreak modelling.

Mayaro virus (MAYV) is an arbovirus that is endemic to tropical forests in Central and South America, particularly within the Amazon basin. In recent years, concern has increased regarding MAYV's ability to invade urban areas and cause epidemics across the region. We conducted a systematic literature review to characterise the evolutionary history of MAYV, its transmission potential, and exposure patterns to the virus. We analysed data from the literature on MAYV infection to produce estimates of key epidemiological parameters, including the generation time and the basic reproduction number, R0. We also estimated the force-of-infection (FOI) in epidemic and endemic settings. Seventy-six publications met our inclusion criteria. Evidence of MAYV infection in humans, animals, or vectors was reported in 14 Latin American countries. Nine countries reported evidence of acute infection in humans confirmed by viral isolation or reverse transcription-PCR (RT-PCR). We identified at least five MAYV outbreaks. Seroprevalence from population based cross-sectional studies ranged from 21% to 72%. The estimated mean generation time of MAYV was 15.2 days (95% CrI: 11.7-19.8) with a standard deviation of 6.3 days (95% CrI: 4.2-9.5). The per-capita risk of MAYV infection (FOI) ranged between 0.01 and 0.05 per year. The mean R0 estimates ranged between 2.1 and 2.9 in the Amazon basin areas and between 1.1 and 1.3 in the regions outside of the Amazon basin. Although MAYV has been identified in urban vectors, there is not yet evidence of sustained urban transmission. MAYV's enzootic cycle could become established in forested areas within cities similar to yellow fever virus.

Lying in wait: the resurgence of dengue virus after the Zika epidemic in Brazil

After the Zika virus (ZIKV) epidemic in the Americas in 2016, both Zika and dengue incidence declined to record lows in many countries in 2017–2018, but in 2019 dengue resurged in Brazil, causing ~2.1 million cases. In this study we use epidemiological, climatological and genomic data to investigate dengue dynamics in recent years in Brazil. First, we estimate dengue virus force of infection (FOI) and model mosquito-borne transmission suitability since the early 2000s. Our estimates reveal that DENV transmission was low in 2017–2018, despite conditions being suitable for viral spread. Our study also shows a marked decline in dengue susceptibility between 2002 and 2019, which could explain the synchronous decline of dengue in the country, partially as a result of protective immunity from prior ZIKV and/or DENV infections. Furthermore, we performed phylogeographic analyses using 69 newly sequenced genomes of dengue virus serotype 1 and 2 from Brazil, and found that the outbreaks in 2018–2019 were caused by local DENV lineages that persisted for 5–10 years, circulating cryptically before and after the Zika epidemic. We hypothesize that DENV lineages may circulate at low transmission levels for many years, until local conditions are suitable for higher transmission, when they cause major outbreaks.

The Effect of Mobility Restrictions on the SARS-CoV-2 Diffusion During the First Wave: What Are the Impacts in Sweden, USA, France and Colombia

Background: The control of human mobility has quickly been targeted as a major leverage to contain the spread of SARS-CoV-2 in a great majority of countries worldwide. Using the anonymised data collected by one of the major social media platforms combined with spatial and temporal Covid-19 data, the objective of this research is to understand how mobility patterns and SARS-CoV-2 diffusion during the first wave are connected in four different countries: the west coast of the USA, Colombia, Sweden and France.Method: To measure mobility patterns during the pandemic, we accessed Facebook mobile users’ data provided within the company’s Data for Good framework through a dedicated platform. Measured every eight hours, they provide the information on how more than the 10 million users moved from a given administrative unit (county in USA, département in France, municipios in Colombia, county in Sweden) to another between two time periods. The number of cases in the unit of origin per week was multiplied by the summed Facebook movements from unit of origin to unit of destination. This thus generated a potential incoming force of infection (FoI) for every unit of destination based on every unit of origin number of cases and incoming mobility. A Generalized linear model (GLM) with a logarithmic Quasi-Poisson distribution was then fitted to the number of cases per week per administrative unit as the response variable with the new number of cases registered in each unit during the previous week, the logFoI from the previous week and their interaction as explanatory variables.Findings: Despite a varying impact of lockdown on mobility reduction in these countries (83% in France and Colombia, 55% in USA, 10% in Sweden), our analyses reveal a high spatial concentration of user’s mobility in all the countries. The Gini index related to the number of incoming individuals per unit was high and stable before, during and after the lockdown (0·95-0·96 in Columbia, 0·74-0·79 in France, 0·72-0·77 in USA and 0·59-0·76 in Sweden). In three of the four countries, the logFoI was an important predictor of the number of cases or infections registered in a week throughout the period. For Colombia the exponential of the regression coefficients related to logFoI was constant, with an average of 1·30 over all the time period. In France, although more variable, the strength of the association was stronger, averaging at 1·47. For these two countries, there is a common temporal tendency with a decrease of the logFoI effect following the first lockdown. In the USA, the effect was very mild, with an average of 1·15 and peaking in June. By comparison the effect was only 1·18 on average for Sweden with confidence intervals often overlapping with 1. Finally, our analyses show that the integration of mobility data considerably improved the epidemiological model (as revealed by the QAIC).Interpretation: Although the impact of the lockdown on the diffusion of SARS-CoV-2 among geographical units was modest, the integration of mobility data considerably improved our understanding of the spatial spread of Covid. Such predictability of mobility patterns and their significant role in viral diffusion could enable optimisation of public health mitigation strategies at a local scale. Administrations can observe changes in mobility patterns, generate vulnerability maps and better locate where to implement disease control measures.Funding Statement: This study was funded by PICS Urb India (CNRS grant).Declaration of Interests: Authors declare no conflict of interests.

Seroprevalence of chikungunya virus infection in India, 2017: a cross-sectional population-based serosurvey

Since its re-emergence in 2005, chikungunya virus (CHIKV) transmission has been documented in most Indian states. Information is scarce regarding the seroprevalence of CHIKV in India. We aimed to estimate the age-specific seroprevalence, force of infection (FOI), and proportion of the population susceptible to CHIKV infection. We did a nationally representative, cross-sectional serosurvey, in which we randomly selected individuals in three age groups (5-8, 9-17, and 18-45 years), covering 240 clusters from 60 selected districts of 15 Indian states spread across all five geographical regions of India (north, northeast, east, south, and west). Age was the only inclusion criterion. We tested serum samples for IgG antibodies against CHIKV. We estimated the weighted age-group-specific seroprevalence of CHIKV infection for each region using the design weight (ie, the inverse of the overall probability of selection of state, district, village or ward, census enumeration block, and individual), adjusting for non-response. We constructed catalytic models to estimate the FOI and the proportion of the population susceptible to CHIKV in each region. From June 19, 2017, to April 12, 2018, we enumerated 117 675 individuals, of whom 77 640 were in the age group of 5-45 years. Of 17 930 randomly selected individuals, 12 300 individuals participated and their samples were used for estimation of CHIKV seroprevalence. The overall prevalence of IgG antibodies against CHIKV in the study population was 18·1% (95% CI 14·2-22·6). The overall seroprevalence was 9·2% (5·4-15·1) among individuals aged 5-8 years, 14·0% (8·8-21·4) among individuals aged 9-17 years, and 21·6% (15·9-28·5) among individuals aged 18-45 years. The seroprevalence was lowest in the northeast region (0·3% [95% CI 0·1-0·8]) and highest in the southern region (43·1% [34·3-52·3]). There was a significant difference in seroprevalence between rural (11·5% [8·8-15·0]) and urban (40·2% [31·7-49·3]) areas (p<0·0001). The seroprevalence did not differ by sex (male 18·8% [95% CI 15·2-23·0] vs female 17·6% [13·2-23·1]; p=0·50). Heterogeneous FOI models suggested that the FOI was higher during 2003-07 in the southern and western region and 2013-17 in the northern region. FOI was lowest in the eastern and northeastern regions. The estimated proportion of the population susceptible to CHIKV in 2017 was lowest in the southern region (56·3%) and highest in the northeastern region (98·0%). CHIKV transmission was higher in the southern, western, and northern regions of India than in the eastern and northeastern regions. However, a higher proportion of the population susceptible to CHIKV in the eastern and northeastern regions suggests a susceptibility of these regions to outbreaks in the future. Our survey findings will be useful in identifying appropriate target age groups and sites for setting up surveillance and for future CHIKV vaccine trials. Indian Council of Medical Research.

Estimating the Force of Infection for Dengue Virus Using Repeated Serosurveys, Ouagadougou, Burkina Faso.

Because of limited data on dengue virus in Burkina Faso, we conducted 4 consecutive age-stratified longitudinal serologic surveys, ≈6 months apart, among persons 1–55 years of age, during June 2015–March 2017, which included a 2016 outbreak. The seroconversion rate before the serosurvey enrollment was estimated by binomial regression, taking age as the duration of exposure, and assuming constant force of infection (FOI) over age and calendar time. We calculated FOI between consecutive surveys and rate ratios for potentially associated characteristics based on seroconversion using the duration of intervals. Among 2,897 persons at enrollment, 66.3% were IgG-positive, and estimated annual FOI was 5.95%. Of 1,269 enrollees participating in all 4 serosurveys, 438 were IgG-negative at enrollment. The annualized FOI ranged from 10% to 20% (during the 2016 outbreak). Overall, we observed high FOI for dengue. These results could support decision-making about control and preventive measures for dengue.

Sex-based differences in clearance of chronic Plasmodium falciparum infection.

Multiple studies have reported a male bias in incidence and/or prevalence of malaria infection in males compared to females. To test the hypothesis that sex-based differences in host-parasite interactions affect the epidemiology of malaria, we intensively followed Plasmodium falciparum infections in a cohort in a malaria endemic area of eastern Uganda and estimated both force of infection (FOI) and rate of clearance using amplicon deep-sequencing. We found no evidence of differences in behavioral risk factors, incidence of malaria, or FOI by sex. In contrast, females cleared asymptomatic infections at a faster rate than males (hazard ratio [HR]=1.82, 95% CI 1.20 to 2.75 by clone and HR = 2.07, 95% CI 1.24 to 3.47 by infection event) in multivariate models adjusted for age, timing of infection onset, and parasite density. These findings implicate biological sex-based differences as an important factor in the host response to this globally important pathogen.

Endemic and Epidemic Human Alphavirus Infections in Eastern Panama: An Analysis of Population-Based Cross-Sectional Surveys.

ABSTRACTMadariaga virus (MADV) has recently been associated with severe human disease in Panama, where the closely related Venezuelan equine encephalitis virus (VEEV) also circulates. In June 2017, a fatal MADV infection was confirmed in a community of Darien Province. We conducted a cross-sectional outbreak investigation with human and mosquito collections in July 2017, where sera were tested for alphavirus antibodies and viral RNA. In addition, by applying a catalytic, force-of-infection (FOI) statistical model to two serosurveys from Darien Province in 2012 and 2017, we investigated whether endemic or epidemic alphavirus transmission occurred historically. In 2017, MADV and VEEV IgM seroprevalences were 1.6% and 4.4%, respectively; IgG antibody prevalences were MADV: 13.2%, VEEV: 16.8%, Una virus (UNAV): 16.0%, and Mayaro virus: 1.1%. Active viral circulation was not detected. Evidence of MADV and UNAV infection was found near households, raising questions about its vectors and enzootic transmission cycles. Insomnia was associated with MADV and VEEV infections, depression symptoms were associated with MADV, and dizziness with VEEV and UNAV. Force-of-infection analyses suggest endemic alphavirus transmission historically, with recent increased human exposure to MADV and VEEV in Aruza and Mercadeo, respectively. The lack of additional neurological cases suggests that severe MADV and VEEV infections occur only rarely. Our results indicate that over the past five decades, alphavirus infections have occurred at low levels in eastern Panama, but that MADV and VEEV infections have recently increased—potentially during the past decade. Endemic infections and outbreaks of MADV and VEEV appear to differ spatially in some locations of eastern Panama.

Comparison of Japanese Encephalitis Force of Infection in Pigs, Poultry and Dogs in Cambodian Villages.

Japanese encephalitis virus (JEV) is the main cause of human viral encephalitis in Asia, with a mortality rate reaching 30%, mostly affecting children. The traditionally described cycle involving wild birds as reservoirs, pigs as amplifying hosts and Culex mosquitoes as vectors is questioned, with increasing evidence of a more complex multi-host system involved in areas where densities of pigs are low, such as in Cambodia. In 2018, we examined pigs, chickens, ducks and dogs from Kandal province, Cambodia, for antibody response against JEV by hemagglutination inhibition and virus neutralization assays. Forces of infection (FOI) for flaviviruses and JEV were estimated per species and per unit of body surface area (BSA). JEV seroprevalence reached 31% (95% CI: 23–41%) in pigs, 1% (95% CI: 0.1–3%) in chickens, 12% (95% CI: 7–19%) in ducks and 35% (95% CI: 28–42%) in dogs. Pigs were most likely to be infected (FOI: 0.09 per month), but the FOI was higher in ducks than in pigs for a given BSA (ratio of 0.13). Dogs had a lower FOI than ducks but a higher FOI than chickens (0.01 per month). For a given BSA, dogs were less likely to be infected than pigs (ratio of 1.9). In Cambodia, the virus may be circulating between multiple hosts. Dogs live in close contact with humans, and estimating their exposure to JEV infection could be a relevant indicator of the risk for humans to get infected, which is poorly known due to underdiagnosis. Understanding the JEV cycle and developing tools to quantify the exposure of humans is essential to adapt and support control measures for this vaccine-preventable disease.

A hybrid model for the effects of treatment and demography on malaria superinfection

As standard mathematical models for the transmission of vector-borne pathogens with weak or no apparent sterilizing immunity, Susceptible-Infected-Susceptible (SIS) systems such as the Ross-Macdonald equations are a useful starting point for modeling the impacts of interventions on prevalence for diseases that cannot superinfect their hosts. In particular, they are parameterizable from quantities we can estimate such as the force of infection (FOI), the rate of natural recovery from a single infection, the treatment rate, and the rate of demographic turnover. However, malaria parasites can superinfect their host which has the effect of increasing the duration of infection before total recovery. Queueing theory has been applied to capture this behavior, but a problem with current queueing models is the exclusion of factors such as demographic turnover and treatment. These factors in particular can affect the entire shape of the distribution of the multiplicity of infection (MOI) generated by the superinfection process, its transient dynamics, and the population mean recovery rate. Here we show the distribution of MOI can be described by an alternative hyper-Poisson distribution. We then couple our resulting equations to a simple vector transmission model, extending previous Ross-Macdonald theory.

Epstein-Barr Virus Seroprevalence and Force of Infection in a Multiethnic Pediatric Cohort, Singapore.

Epstein-Barr virus (EBV) spreads through bodily fluids, especially saliva, and can cause infectious mononucleosis. EBV immunity and infection status can be assessed by testing EBV viral capsid antigen and nuclear antigen (EBNA) antibodies in blood. In this study, we investigated the seroprevalence and force of infection (FOI) of EBV antibodies among children and young people in 3 ethnic groups in Singapore. Eight hundred ninety-six residual serum samples at a tertiary hospital were tested for viral capsid antigen (IgG and IgM) and EBNA IgG antibodies using Abbott Architect assays. We calculated the EBV seroprevalence using catalytic models to estimate the EBV force of infection from age-stratified seroprevalence data, both overall and by ethnic group. Overall seropositivity was 68.3% (n = 612). Seropositivity was higher in Malays (81.8%) compared with both Chinese (64.2%) and Indians (58.4%). EBV FOI was consistently higher in Malays, with an estimated annual rate of seroconversion of 25% in children 1 year, of age compared with 14% among Chinese and Indians at the same age. The seroprevalence patterns of EBV antibodies in the Chinese and Indian, but not Malay children in Singapore by 19 years of age resemble those previously reported in developed countries. Ideally, any future EBV vaccination strategy would need to target infants <1 year of age for maximum population benefit.

Estimated dengue force of infection and burden of primary infections among Indian children

BackgroundComprehensive, age-stratified dengue surveillance data are unavailable from India and many more dengue cases occur than are reported. Additional information on dengue transmission dynamics can inform understanding of disease endemicity and infection risk.MethodsUsing age-stratified dengue IgG seroprevalence data from 2556 Indian children aged 5–10 years, we estimated annual force of infection (FOI) at each of 6 sites using a binomial regression model. We estimated the ages by which 50 and 70% of children were first infected; and predicted seroprevalence in children aged 1–10 years assuming constant force-of-infection. Applying these infection rates to national census data, we then calculated the number of primary dengue infections occurring, annually, in Indian children.ResultsAnnual force-of-infection at all sites combined was 11.9% (95% CI 8.8–16.2), varying across sites from 3.5% (95% CI 2.8–4.4) to 21.2% (95% CI 18.4–24.5). Overall, 50 and 70% of children were infected by 5.8 (95% CI 4.3–7.9) and 10.1 (95% CI 7.4–13.7) years respectively. In all sites except Kalyani, > 70% of children had been infected before their 11th birthday, and goodness-of-fit statistics indicated a relatively constant force-of-infection over time except at two sites (Wardha and Hyderabad). Nationwide, we estimated 17,013,527 children (95% CI: 14,518,438- 19,218,733), equivalent to 6.5% of children aged < 11 years, experience their first infection annually.ConclusionsDengue force-of-infection in India is comparable to other highly endemic countries. Significant variation across sites exists, likely reflecting local epidemiological variation. The number of annual primary infections is indicative of a significant, under-reported burden of secondary infections and symptomatic episodes.Trial registrationRegistered retrospectively with clinicaltrials.gov (NCT01477671; 18/11/2011) and clinical trials registry of India (ctri.nic.in; CTRI/2011/12/002243; 15/12/2011). Date of enrollment of 1st subject: 22/9/2011.

Chagas disease in the Bolivian Chaco: Persistent transmission indicated by childhood seroscreening study

BackgroundScreening for Trypanosoma cruzi infection was performed amongst children in a rural community in the Bolivian Chaco, an area known for high prevalence. The force of infection (FOI) was estimated. MethodsA total of 423 children attending the local school were screened using the Chagas Detect Plus (CDP) rapid test (InBios International, Inc.). CDP-positive specimens were further tested by indirect haemagglutination assay (IHA) and Wiener Recombinante v3.0 ELISA. A catalytic model was used to estimate FOI. ResultsConfirmed seroprevalence was 0.22, rising steeply with age. The mean age of seropositive individuals was 13 years. The calculated specificity of the rapid test was 91.9%. The annual incidence estimated from the FOI was 0.021. ConclusionsThis study demonstrates persistent transmission and continuing high levels of T. cruzi infection in the Bolivian Chaco, and highlights the practicality of school-based screening.

Serological Epidemiology of Foot-and-mouth Disease among Sedentary Mixed-species Herds in Adamawa Region, Cameroon

Foot-and-mouth disease (FMD) is an economically important viral disease of domestic animals and wildlife. High circulation occurs during outbreaks but little is known about the current transmission dynamics in sedentary cattle and sheep herds. To investigate on this, samples from cattle and sheep located in the Vina Division of the Adamawa region of Cameroon, during FMD outbreaks were collected. Non-Structural Protein (NSP) and antigen detecting/serotyping FMD ELISAs were used for sample screening. The NSP serological data of cattle was used to estimate transmission parameters in catalytic and reverse catalytic models. The Akaike’s Information Criteria (AIC) revealed the reverse catalytic model as the most parsimonious for the NSP serological data and was used to estimate the force of infection (FOI), the rate of waning immunity and to estimate historic periods of sustained transmission. Four serological types of FMD notably O, A, SAT 1 and SAT 2 were identified from cattle vesicular epithelia tissues. Seroprevalence findings revealed 65.14% and 15.71% FMDV antibodies in cattle and sheep respectively with highest prevalence in both populations occurring in Mbidjoro. The FOI (λ) in sedentary herds was constant; the rate of waning immunity (ω) was 0.32 meaning cattle are generally immune for 3.12 years post natural infection. The reproductive number (Rt) was 7.33, meaning approximately 87% of cattle always need to be effectively immunized to prevent outbreaks. Therefore, FMD circulates in sedentary cattle and sheep populations in the study area with four serological types detected in cattle.