Reconciling heterogeneous dengue virus infection risk estimates from different study designs.

Uncovering rates at which susceptible individuals become infected with a pathogen, i.e. the force of infection (FOI), is essential for assessing transmission risk and reconstructing distribution of immunity in a population. For dengue, reconstructing exposure and susceptibility statuses from the measured FOI is of particular significance as prior exposure is a strong risk factor for severe disease. FOI can be measured via many study designs. Longitudinal serology are considered gold standard measurements, as they directly track the transition of seronegative individuals to seropositive due to incident infections (seroincidence). Cross-sectional serology can provide estimates of FOI by contrasting seroprevalence across ages. Age of reported cases can also be used to infer FOI. Agreement of these measurements, however, have not been assessed. Using 26 years of data from cohort studies and hospital-attended cases from Kamphaeng Phet province, Thailand, we found FOI estimates from the three sources to be highly inconsistent. Annual FOI estimates from seroincidence was 2.46 to 4.33-times higher than case-derived FOI. Correlation between seroprevalence-derived and case-derived FOI was moderate (correlation coefficient=0.46) and no systematic bias. Through extensive simulations and theoretical analysis, we show that incongruences between methods can result from failing to account for dengue antibody kinetics, assay noise, and heterogeneity in FOI across ages. Extending standard inference models to include these processes reconciled the FOI and susceptibility estimates. Our results highlight the importance of comparing inferences across multiple data types to uncover additional insights not attainable through a single data type/analysis.

Climate, demography, immunology, and virology combine to drive two decades of dengue virus dynamics in Cambodia.

The incidence of dengue virus disease has increased globally across the past half-century, with highest number of cases ever reported in 2019 and again in 2023. We analyzed climatological, epidemiological, and phylogenomic data to investigate drivers of two decades of dengue in Cambodia, an understudied endemic setting. Using epidemiological models fit to a 19-y dataset, we first demonstrate that climate-driven transmission alone is insufficient to explain three epidemics across the time series. We then use wavelet decomposition to highlight enhanced annual and multiannual synchronicity in dengue cycles between provinces in epidemic years, suggesting a role for climate in homogenizing dynamics across space and time. Assuming reported cases correspond to symptomatic secondary infections, we next use an age-structured catalytic model to estimate a declining force of infection for dengue through time, which elevates the mean age of reported cases in Cambodia. Reported cases in >70-y-old individuals in the 2019 epidemic are best explained when also allowing for waning multitypic immunity and repeat symptomatic infections in older patients. We support this work with phylogenetic analysis of 192 dengue virus (DENV) genomes that we sequenced between 2019 and 2022, which document emergence of DENV-2 Cosmopolitan Genotype-II into Cambodia. This lineage demonstrates phylogenetic homogeneity across wide geographic areas, consistent with invasion behavior and in contrast to high phylogenetic diversity exhibited by endemic DENV-1. Finally, we simulate an age-structured, mechanistic model of dengue dynamics to demonstrate how expansion of an antigenically distinct lineage that evades preexisting multitypic immunity effectively reproduces the older-age infections witnessed in our data.

Rubella immunity among pregnant women and the burden of congenital rubella syndrome (CRS) in India, 2022.

BACKGROUND: India aims to eliminate rubella and congenital rubella syndrome (CRS) by 2023. We conducted serosurveys among pregnant women to monitor the trend of rubella immunity and estimate the CRS burden in India following a nationwide measles and rubella vaccination campaign. METHODS: We surveyed pregnant women at 13 sentinel sites across India from Aug to Oct 2022 to estimate seroprevalence of rubella IgG antibodies. Using age-specific seroprevalence data from serosurveys conducted during 2017/2019 (prior to and during the vaccination campaign) and 2022 surveys (after the vaccination campaign), we developed force of infection (FOI) models and estimated incidence and burden of CRS. RESULTS: In 2022, rubella seroprevalence was 85.2% (95% CI: 84.0, 86.2). Among 10 sites which participated in both rounds of serosurveys, the seroprevalence was not different between the two periods (pooled prevalence during 2017/2019: 83.5%, 95% CI: 82.1, 84.8; prevalence during 2022: 85.1%, 95% CI: 83.8, 86.3). The estimated annual incidence of CRS during 2017/2019 in India was 218.3 (95% CI: 209.7, 226.5) per 100, 000 livebirths, resulting in 47,120 (95% CI: 45,260, 48,875) cases of CRS every year. After measles-rubella (MR) vaccination campaign, the estimated incidence of CRS declined to 5.3 (95% CI: 0, 21.2) per 100,000 livebirths, resulting in 1141 (95% CI: 0, 4,569) cases of CRS during the post MR-vaccination campaign period. CONCLUSION: The incidence of CRS in India has substantially decreased following the nationwide MR vaccination campaign. About 15% of women in childbearing age in India lack immunity to rubella and hence susceptible to rubella infection. Since there are no routine rubella vaccination opportunities for this age group under the national immunization program, it is imperative to maintain high rates of rubella vaccination among children to prevent rubella virus exposure among women of childbearing age susceptible for rubella.

Analysing HCV incidence trends in people who inject drugs using serial behavioural and seroprevalence data: A modelling study.

INTRODUCTION: The introduction of new direct-acting antivirals for hepatitis C virus (HCV) infection, has enabled the formulation of a HCV elimination strategy led by the World Health Organisation (WHO). Guidelines for elimination of HCV target a reduction in incidence, but this is difficult to measure and needs estimating. METHODS: Serial cross-sectional bio-behavioural sero-surveys provide information on an individual's infection status and duration of exposure and how these change over time. These data can be used to estimate the rate of first infection through appropriate statistical models. This study utilised updated HCV seroprevalence information from the Unlinked Anonymous Monitoring survey, an annual survey of England, Wales and Northern Ireland monitoring the prevalence of blood borne viruses in people who inject drugs. Flexible parametric and semiparametric approaches, including fractional polynomials and splines, for estimating incidence rates by exposure time and survey year were implemented and compared. RESULTS: Incidence rates were shown to peak in those recently initiating injecting drug use at approximately 0.20 infections per person-year followed by a rapid reduction in the subsequent few years of injecting to approximately 0.05 infections per person-year. There was evidence of a rise in incidence rates for recent initiates between 2011 and 2020 from 0.17 infections per person-year (95 % CI, 0.16-0.19) to 0.26 infections per person-year (0.23-0.30). In those injecting for longer durations, incidence rates were stable over time. CONCLUSIONS: Fractional polynomials provided an adequate fit with relatively few parameters, but splines may be preferable to ensure flexibility, in particular, to detect short-term changes in the rate of first infection over time that may be a result of treatment effects. Although chronic HCV prevalence has declined with treatment scale up over 2016-2020, there is no evidence yet of a corresponding fall in the rate of first infection. Seroprevalence and risk behaviour data can be used to estimate and monitor HCV incidence, providing insight into progress towards WHO defined elimination of HCV.

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands.

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020-February 2021). We estimated average annual concentrations of PM10, PM2.5 and NO2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals' average exposure to PM10, PM2.5 and NO2 in the three years before the pandemic (2017-2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source.

The burden of dengue and force of infection among children in Kerala, India; seroprevalence estimates from Government of Kerala-WHO Dengue study.

Background: Dengue shows high geographic heterogeneity within and across endemic countries. In the context of increasing burden and predicted outbreaks due to climate change, understanding the heterogeneity will enable us to develop region specific targeted interventions, including vaccination. World Health Organisation (WHO) suggests standard methodologies to study the burden and heterogeneity at national and subnational levels. Regional studies with robust and standard methodology to capture heterogeneity are scarce. We estimated the seroprevalence of dengue in children aged 9-12 years and the force of infection in Kerala, India, from where Zika cases also have been reported recently. Methods: We conducted a school-based cross-sectional survey in 38 clusters; selected by stratified random sampling, representing rural, urban, high burden and low-burden administrative units. Validation of Indirect IgG ELISA was done by Plaque Reduction Neutralization Test (PRNT90) using the local isolates of all four serotypes. Force of infection (FOI) was estimated using the WHO-FOI calculator. We conducted a follow-up survey among a subsample of seronegative children, to estimate the rate of sero-conversion. Results: Among 5236 children tested, 1521 were positive for anti-dengue IgG antibody. The overall seroprevalence in the state was 29% (95% CI 24.1-33.9). The validity corrected seroprevalence was 30.9% in the overall sample, 46.9% in Thiruvananthapuram, 26.9% in Kozhikkode and 24.9% in Kollam. Age-specific seroprevalence increased with age; 25.7% at 9 years, 29.5% at 10 years, 30.9% at 11 years and 33.9% at 12 years. Seroprevalence varied widely across clusters (16.1%-71.4%). The estimated force of infection was 3.3/100 person-years and the seroconversion rate was 4.8/100 person-years. 90% of children who tested positive were not aware of dengue infection. All the four serotypes were identified in PRNT and 40% of positive samples had antibodies against multiple serotypes. Interpretation: The study validates the WHO methodology for dengue serosurveys and confirms its feasibility in a community setting. The overall seroprevalence in the 9-12 year age group is low to moderate in Kerala; there are regional variations; high burden and low burden clusters co-exist in the same districts. The actual burden of dengue exceeds the reported numbers. Heterogeneity in prevalence, the high proportion of inapparent dengue and the hyperendemic situation suggest the need for region-specific and targeted interventions, including vaccination. Funding: World Health Organization.

Age-time-specific transmission of hand-foot-and-mouth disease enterovirus serotypes in Vietnam: A catalytic model with maternal immunity.

Hand, foot and mouth disease (HFMD) is highly prevalent in the Asia Pacific region, particularly in Vietnam. To develop effective interventions and efficient vaccination programs, we inferred the age-time-specific transmission patterns of HFMD serotypes enterovirus A71 (EV-A71), coxsackievirus A6 (CV-A6), coxsackievirus A10 (CV-A10), coxsackievirus A16 (CV-A16) in Ho Chi Minh City, Vietnam from a case data collected during 2013-2018 and a serological survey data collected in 2015 and 2017. We proposed a catalytic model framework with good adaptability to incorporate maternal immunity using various mathematical functions. Our results indicate the high-level transmission of CV-A6 and CV-A10 which is not obvious in the case data, due to the variation of disease severity across serotypes. Our results provide statistical evidence supporting the strong association between severe illness and CV-A6 and EV-A71 infections. The HFMD dynamic pattern presents a cyclical pattern with large outbreaks followed by a decline in subsequent years. Additionally, we identify the age group with highest risk of infection as 1-2 years and emphasise the risk of future outbreaks as over 50% of children aged 6-7 years were estimated to be susceptible to CV-A16 and EV-A71. Our study highlights the importance of multivalent vaccines and active surveillance for different serotypes, supports early vaccination prior to 1 year old, and points out the potential utility for vaccinating children older than 5 years old in Vietnam.

Can incorporating genotyping data into efficacy estimators improve efficiency of early phase malaria vaccine trials?

BACKGROUND: Early phase malaria vaccine field trials typically measure malaria infection by PCR or thick blood smear microscopy performed on serially sampled blood. Vaccine efficacy (VE) is the proportion reduction in an endpoint due to vaccination and is often calculated as VEHR = 1-hazard ratio or VERR = 1-risk ratio. Genotyping information can distinguish different clones and distinguish multiple infections over time, potentially increasing statistical power. This paper investigates two alternative VE endpoints incorporating genotyping information: VEmolFOI, the vaccine-induced proportion reduction in incidence of new clones acquired over time, and VEC, the vaccine-induced proportion reduction in mean number of infecting clones per exposure. METHODS: Power of VEmolFOI and VEC was compared to that of VEHR and VERR by simulations and analytic derivations, and the four VE methods were applied to three data sets: a Phase 3 trial of RTS,S malaria vaccine in 6912 African infants, a Phase 2 trial of PfSPZ Vaccine in 80 Burkina Faso adults, and a trial comparing Plasmodium vivax incidence in 466 Papua New Guinean children after receiving chloroquine + artemether lumefantrine with or without primaquine (as these VE methods can also quantify effects of other prevention measures). By destroying hibernating liver-stage P. vivax, primaquine reduces subsequent reactivations after treatment completion. RESULTS: In the trial of RTS,S vaccine, a significantly reduced number of clones at first infection was observed, but this was not the case in trials of PfSPZ Vaccine or primaquine, although the PfSPZ trial lacked power to show a reduction. Resampling smaller data sets from the large RTS,S trial to simulate phase 2 trials showed modest power gains from VEC compared to VEHR for data like those from RTS,S, but VEC is less powerful than VEHR for trials in which the number of clones at first infection is not reduced. VEmolFOI was most powerful in model-based simulations, but only the primaquine trial collected enough serial samples to precisely estimate VEmolFOI. The primaquine VEmolFOI estimate decreased after most control arm liver-stage infections reactivated (which mathematically resembles a waning vaccine), preventing VEmolFOI from improving power. CONCLUSIONS: The power gain from the genotyping methods depends on the context. Because input parameters for early phase power calculations are often uncertain, these estimators are not recommended as primary endpoints for small trials unless supported by targeted data analysis. TRIAL REGISTRATIONS: NCT00866619, NCT02663700, NCT02143934.

Can incorporating genotyping data into efficacy estimators improve efficiency of early phase malaria vaccine trials?

Background: Early phase malaria vaccine field trials typically measure malaria infection by PCR or thick blood smear microscopy performed on serially sampled blood. Vaccine efficacy (VE) is the proportion reduction in an endpoint due to vaccination and is often calculated as VEHR=1 - hazard ratio or VERR=1 - risk ratio. Genotyping information can distinguish different clones and distinguish multiple infections over time, potentially increasing statistical power. This paper investigates two alternative VE endpoints incorporating genotyping information: VEmolFOI, the vaccine-induced proportion reduction in incidence of new clones acquired over time, and VEC, the vaccine-induced proportion reduction in mean number of infecting clones per exposure. Methods: We used simulations and analytic derivations to compare power of these methods to VEHR and VERR and applied them to three data sets: a Phase 3 trial of RTS,S malaria vaccine in 6912 African infants, a Phase 2 trial of PfSPZ Vaccine in 80 Burkina Faso adults, and a trial comparing Plasmodium vivax incidence in 466 Papua New Guinean children after receiving chloroquine + artemether lumefantrine with or without primaquine (as these VE methods can also quantify effects of other prevention measures). By destroying hibernating liver-stage P. vivax, primaquine reduces subsequent reactivations after treatment completion. Results: The RTS,S vaccine significantly reduced the number of clones at first infection, but PfSPZ vaccine and primaquine did not. Resampling smaller data sets from the large RTS,S trial to simulate phase 2 trials showed modest power gains from VEC compared to VEHR for data like RTS,S, but VEC is less powerful than VEHR for vaccines which do not reduce the number of clones at first infection. VEmolFOI was most powerful in model-based simulations, but only the primaquine trial collected enough serial samples to precisely estimate VEmolFOI. The primaquine VEmolFOI estimate decreased after most control arm liver-stage infections reactivated (which mathematically resembles a waning vaccine), preventing VEmolFOI from improving power. Conclusions: The power gain from the genotyping methods depends on the context. Because input parameters for early phase power calculations are often uncertain, we recommend against these estimators as primary endpoints for small trials unless supported by targeted data analysis. Trial registrations: NCT00866619, NCT02663700, NCT02143934.

Seroprevalence of dengue virus infection in Pune City in India, 2019: A decadal change.

BACKGROUND: The burden of dengue infection needs to be monitored along with tracking of the changes in dengue virus (DENV) transmission intensity for vaccine introduction decisions. METHODS: The seroprevalence of dengue was investigated in Pune City in India, in early 2019 using 1654 sera from apparently healthy human participants enrolled randomly through multistage cluster sampling. We used 797 retrospective human sera from late 2009 for comparison. All sera were assessed for the presence of dengue-specific IgG antibodies. A subset (n = 230) was tested for serotype-specific plaque reduction-neutralizing antibodies against all four serotypes. RESULTS: The dengue IgG seroprevalence of 62.9% (95% CI 59.4-66.1) in 2009 increased to 88.4% (95% CI 86.8-89.8) in 2019. Age-stratified dengue seroprevalence revealed a gradual increase in IgG seropositivity from 70.1% in 0-9 years to 85.0% in 10-19 years. The annual probability of dengue infection estimated as a force of infection was 4.1 (95% CI 3.8-4.5) in 2009, which increased to 10.9 (95% CI 10.2-11.6) in 2019. Analysis of dengue serotype-specific neutralizing antibodies revealed DENV-3 as the dominant serotype. The age of exposure to at least one dengue serotype was reduced in 2019 over 2009. CONCLUSIONS: There was a significant increase in the intensity of dengue virus transmission in Pune City over the decade. Since over 85% of the participants above nine years of age had exposure to DENV by 2019, dengue vaccine introduction can be considered. Moreover, such repeated serosurveys in different regions might inform about the readiness of the population for dengue vaccination.

From serological surveys to disease burden: a modelling pipeline for Chagas disease.

In 2012, the World Health Organization (WHO) set the elimination of Chagas disease intradomiciliary vectorial transmission as a goal by 2020. After a decade, some progress has been made, but the new 2021-2030 WHO roadmap has set even more ambitious targets. Innovative and robust modelling methods are required to monitor progress towards these goals. We present a modelling pipeline using local seroprevalence data to obtain national disease burden estimates by disease stage. Firstly, local seroprevalence information is used to estimate spatio-temporal trends in the Force-of-Infection (FoI). FoI estimates are then used to predict such trends across larger and fine-scale geographical areas. Finally, predicted FoI values are used to estimate disease burden based on a disease progression model. Using Colombia as a case study, we estimated that the number of infected people would reach 506 000 (95% credible interval (CrI) = 395 000-648 000) in 2020 with a 1.0% (95%CrI = 0.8-1.3%) prevalence in the general population and 2400 (95%CrI = 1900-3400) deaths (approx. 0.5% of those infected). The interplay between a decrease in infection exposure (FoI and relative proportion of acute cases) was overcompensated by a large increase in population size and gradual population ageing, leading to an increase in the absolute number of Chagas disease cases over time. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.

Crayfish population size under different routes of pathogen transmission.

We present an epidemiological model for the crayfish plague, a disease caused by an invasive oomycete Aphanomyces astaci, and its general susceptible freshwater crayfish host. The pathogen shows high virulence with resulting high mortality rates in freshwater crayfishes native to Europe, Asia, Australia, and South America. The crayfish plague occurrence shows complicated dynamics due to the several types of possible infection routes, which include cannibalism and necrophagy. We explore this complexity by addressing the roles of host cannibalism and the multiple routes of transmission through (1) environment, (2) contact, (3) cannibalism, and (4) scavenging of infected carcasses. We describe a compartment model having six classes of crayfish and a pool of crayfish plague spores from a single nonevolving strain. We show that environmental transmission is the decisive factor in the development of epidemics. Compared with a pathogen-free crayfish population, the presence of the pathogen with a low environmental transmission rate, regardless of the contact transmission rate, decreases the crayfish population size with a low risk of extinction. Conversely, a high transmission rate could drive both the crayfish and pathogen populations to extinction. High contact transmission rate with a low but nonzero environmental transmission rate can have mixed outcomes from extinction to large healthy population, depending on the initial values. Scavenging and cannibalism have a relevant role only when the environmental transmission rate is low, but scavenging can destabilize the system by transmitting the pathogen from a dead to a susceptible host. To the contrary, cannibalism stabilizes the dynamics by decreasing the proportion of infected population. Our model provides a simple tool for further analysis of complex host parasite dynamics and for the general understanding of crayfish disease dynamics in the wild.

Age-specific transmission for different virus serotypes of hand, foot and mouth disease and the impact of interventions in East China, 2009-2015.

Background: Hand, foot and mouth disease (HFMD) remains an important public health problem in China. Understandings of age-specific transmission for different virus serotypes of the disease and assessment of non-pharmaceutical interventions (NPI) for HFMD are helpful for disease control, but they have been seldom considered. Here we further investigate transmission dynamics of HFMD and quantify the effects of NPIs and vaccination on the disease transmission. Methods: We extracted information of reported HFMD cases from 2009 to 2015 in East China. Age-specific force of infection (FoI) was used to describe the transmission characteristics for serotypes (EV-A71, CV-A16 and other enterovirus). We used an age-structured Susceptible-Exposed-Infectious-Removed (SEIR) model to simulate how interventions affect HFMD outbreaks. Results: 4,096,270 HFMD cases were included, and 160619 cases were confirmed for virus serotypes. The peaks of infections always occurred in even-numbered years. CV-A16 and EV-A71 showed a similar trend, children aged 1 or 2 years generally had the highest FoI, but there were no clear patterns for other enterovirus. Simulations showed that school break could dramatically decline the average incidence. When combined with social interventions, it would further reduce the incidence, but the effect is not apparent. When vaccine rate is over or equal to 20%, the incidence would be lower than taking NPIs. Conclusion: More attention should be paid to children under 2 years of age in the prevention and control of HFMD. Compared to NPIs, vaccination is more effective.

Seroepidemiology of Borrelia burgdorferi s.l. among German National Cohort (NAKO) Participants, Hanover.

Lyme borreliosis is the leading tick-related illness in Europe, caused by Borrelia Burgdorferi s.l. Lower Saxony, Germany, including its capital, Hanover, has a higher proportion of infected ticks than central European countries, justifying a research focus on the potential human consequences. The current knowledge gap on human incident infections, particularly in Western Germany, demands serological insights, especially regarding a potentially changing climate-related tick abundance and activity. We determined the immunoglobulin G (IgG) and immunoglobulin M (IgM) serostatuses for 8009 German National Cohort (NAKO) participants from Hanover, examined in 2014-2018. We used an enzyme-linked immunosorbent assay (ELISA) as the screening and a line immunoblot as confirmation for the Borrelia Burgdorferi s.l. antibodies. We weighted the seropositivity proportions to estimate general population seropositivity and estimated the force of infection (FOI). Using logistic regression, we investigated risk factors for seropositivity. Seropositivity was 3.0% (IgG) and 2.1% (IgM). The FOI varied with age, sharply increasing in participants aged ≥40 years. We confirmed advancing age and male sex as risk factors. We reported reduced odds for seropositivity with increasing body mass index and depressive symptomatology, respectively, pointing to an impact of lifestyle-related behaviors. The local proportion of seropositive individuals is comparable to previous estimates for northern Germany, indicating a steady seroprevalence.

Irrigation-Induced Environmental Changes Sustain Malaria Transmission and Compromise Intervention Effectiveness.

BACKGROUND: Irrigated agriculture enhances food security, but it potentially promotes mosquito-borne disease transmission and affects vector intervention effectiveness. This study was conducted in the irrigated and nonirrigated areas of rural Homa Bay and Kisumu Counties, Kenya. METHODS: We performed cross-sectional and longitudinal surveys to determine Plasmodium infection prevalence, clinical malaria incidence, molecular force of infection (molFOI), and multiplicity of infection. We examined the impact of irrigation on the effectiveness of the new interventions. RESULTS: We found that irrigation was associated with >2-fold higher Plasmodium infection prevalence and 3-fold higher clinical malaria incidence compared to the nonirrigated area. Residents in the irrigated area experienced persistent, low-density parasite infections and higher molFOI. Addition of indoor residual spraying was effective in reducing malaria burden, but the reduction was more pronounced in the nonirrigated area than in the irrigated area. CONCLUSIONS: Our findings collectively suggest that irrigation may sustain and enhance Plasmodium transmission and affects intervention effectiveness.

Targeted sampling reduces the uncertainty in force of infection estimates from serological surveillance.

Age bins are frequently used in serological studies of infectious diseases in wildlife to deal with uncertainty in the age of sampled animals. This study analyzed how age binning and targeted sampling in serological surveillance affect the width of the 95% confidence interval (CI) of the estimated force of infection (FOI) of infectious diseases. We indicate that the optimal target population with the narrowest 95% CI differs depending on the expected FOI using computer simulations and mathematical models. In addition, our findings show that we can substantially reduce the number of animals required to infer transmission risk by tailoring targeted, age-based sampling to specific epidemiological situations.

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.

Influenza A virus transmission in swine farms and during transport in the swine supply chain.

The last influenza pandemic in 2009 emerged from swine and surveillance of swine influenza is important for pandemic preparedness. Movement of swine during husbandry, trade or marketing for slaughter provide opportunities for transfer and genetic reassortment of swine influenza viruses. Over 90% of the swine slaughtered at the central swine abattoir in Hong Kong are imported from farms located in multiple provinces in mainland China. There is opportunity for virus cross-infection during this transport and slaughter process. Of the 26,980 swabs collected in the slaughterhouse in Hong Kong from 5 January 2012 to 15 December 2016, we analysed sequence data on influenza A (H3N2) virus isolates (n = 174) in conjunction with date of sampling and originating farm. Molecular epidemiology provided evidence of virus cross-infection between swine originating from different farms during transport. The findings are also suggestive of a virus lineage persisting in a swine farm for over 2 years, although the lack of information on management practices at farm-level means that alternative explanations cannot be excluded. We used virus serology and isolation data from 4226 pairs of linked serum and swabs collected from the same pig at slaughter from swine originating from Guangdong Province to compare the force of infection (FOI) during transport and within farms. The mean weekly FOI during transport was λt  = 0.0286 (95% CI = 0.0211-0.0391) while the weekly FOI in farms was λf = 0.0089 (95% CI = 0.0084-0.0095), assuming a possible exposure duration in farm of 28 weeks, suggesting increased FOI during the transport process. Pigs sourced from farms with high seroprevalence were found to be a significant risk factor (adjusted OR = 2.24, p value = .015) for infection of imported pigs during transport by multivariable logistic regression analysis, whereas pigs with HAI titre of ≥1:40 were associated with a substantial reduction in infection risk by 67% (p value = 0.012). Transport may increase virus cross-infection rates and provide opportunities for virus reassortment potentially increasing zoonotic risk to those involved in the transportation and slaughtering processes.

Mathematical analysis of a SIPC age-structured model of cervical cancer.

Human Papillomavirus (HPV), which is the main causal factor of cervical cancer, infects normal cervical cells on the specific cell's age interval, i.e., between the G1 to S phase of cell cycle. Hence, the spread of the viruses in cervical tissue not only depends on the time, but also the cell age. By this fact, we introduce a new model that shows the spread of HPV infections on the cervical tissue by considering the age of cells and the time. The model is a four dimensional system of the first order partial differential equations with time and age independent variables, where the cells population is divided into four sub-populations, i.e., susceptible cells, infected cells by HPV, precancerous cells, and cancer cells. There are two types of the steady state solution of the system, i.e., disease-free and cancerous steady state solutions, where the stability is determined by using Fatou's lemma and solving some integral equations. In this case, we use a non-standard method to calculate the basic reproduction number of the system. Lastly, we use numerical simulations to show the dynamics of the age-structured system.

Assessing the role of multiple mechanisms increasing the age of dengue cases in Thailand.

The mean age of dengue hemorrhagic fever (DHF) cases increased considerably in Thailand from 8.1 to 24.3 y between 1981 and 2017 (mean annual increase of 0.45 y). Alternative proposed explanations for this trend, such as changes in surveillance practices, reduced mosquito­human contact, and shifts in population demographics, have different implications for global dengue epidemiology. To evaluate the contribution of each of these hypothesized mechanisms to the observed data, we developed 20 nested epidemiological models of dengue virus infection, allowing for variation over time in population demographics, infection hazards, and reporting rates. We also quantified the effect of removing or retaining each source of variation in simulations of the age trajectory. Shifts in the age structure of susceptibility explained 58% of the observed change in age. Adding heterogeneous reporting by age and reductions in per-serotype infection hazard to models with shifts in susceptibility explained an additional 42%. Reductions in infection hazards were mostly driven by changes in the number of infectious individuals at any time (another consequence of shifting age demographics) rather than changes in the transmissibility of individual infections. We conclude that the demographic transition drives the overwhelming majority of the observed change as it changes both the age structure of susceptibility and the number of infectious individuals. With the projected Thai population age structure, our results suggest a continuing increase in age of DHF cases, shifting the burden toward individuals with more comorbidity. These insights into dengue epidemiology may be relevant to many regions of the globe currently undergoing comparable changes in population demographics.