Force Of Infection Research Articles

Force of Infection (FOI) and Multiplicity of Infection (MOI) in Plasmodium falciparum Infected Children Aged 1.5-12 Years Living in the Malaria Endemic Area of Banfora, Burkina Faso.

The aim of this study was to explore molecular measures of P. falciparum malaria burden (FOI and MOI) in the context of seasonal malaria chemoprevention. We analyzed malaria cases collected as part of a longitudinal cohort study. The cohort included P. falciparum-negative children aged 1.5 to 12, as confirmed by PCR 21 days after a radical cure using DHA-PQ or AS. Children were followed up for six months using active and passive case detection methods. At each visit, dried blood spots and blood smears were collected by finger prick, along with clinical data. Parasite DNA was extracted and analyzed by nested PCR for detection and genotyping of P. falciparum parasites. A total of 458 P. falciparum isolates collected during follow-up from October 2020 to March 2021 were genotyped. During the follow-up, children contracted 1.05 (95% IC [0.81-1.30]) new P. falciparum infections/child/time of exposure, and the MOI value was 3.00 (SD 1.60). Age is a protective factor (IRR: 0.74; 95% CI: 0.61, 0.90) against the occurrence of an episode of malaria, unlike an increase in MOI (IRR: 1.63; 95% CI: 1.04, 1.99), which is a favorable factor (p < 0.05). This study confirms the reduction in malaria transmission in our study area, probably due to the massive deployment of control tools.

Estimating the force of infection of four dengue serotypes from serological studies in two regions of Vietnam.

Dengue is endemic in Vietnam with circulation of all four serotypes (DENV1-4) all year-round. It is hard to estimate the disease's true serotype-specific transmission patterns from cases due to its high asymptomatic rate, low reporting rate and complex immunity and transmission dynamics. Seroprevalence studies have been used to great effect for understanding patterns of dengue transmission. We tested 991 population serum samples (ages 1-30 years, collected 2013 to 2017), 531 from Ho Chi Minh City and 460 from Khanh Hoa in Vietnam, using a flavivirus protein microarray assay. By applying our previously developed inference framework to the antibody profiles from this assay, we can (1) determine proportions of a population that have not been infected or infected, once, or more than once, and (2) infer the infecting serotype in those infected once. With these data, we then use mathematical models to estimate the force of infection (FOI) for all four DENV serotypes in HCMC and KH over 35 years up to 2017. Models with time-varying or serotype-specific DENV FOI assumptions fit the data better than constant FOI. Annual dengue FOI ranged from 0.005 (95%CI: 0.003-0.008) to 0.201 (95%CI: 0.174-0.228). FOI varied across serotypes, higher for DENV1 (95%CI: 0.033-0.048) and DENV2 (95%CI: 0.018-0.039) than DENV3 (95%CI: 0.007-0.010) and DENV4 (95%CI: 0.010-0.016). The use of the PMA on serial age-stratified cross-sectional samples increases the amount of information on transmission and population immunity, and should be considered for future dengue serological surveys, particularly to understand population immunity given vaccines with differential efficacy against serotypes, however, there remains limits to what can be inferred even using this assay.

Drivers and epidemiological patterns of West Nile virus in Serbia.

West Nile virus (WNV) is an emerging mosquito-borne pathogen in Serbia, where it has been detected as a cause of infection in humans since 2012. We analyzed and modelled WNV transmission patterns in the country between 2012 and 2023. We applied a previously developed modelling approach to quantify epidemiological parameters of interest and to identify the most important environmental drivers of the force of infection (FOI) by means of statistical analysis in the human population in the country. During the study period, 1,387 human cases were recorded, with substantial heterogeneity across years. We found that spring temperature is of paramount importance for WNV transmission, as FOI magnitude and peak timing are positively associated with it. Furthermore, FOI is also estimated to be greater in regions with a larger fraction of older adult people, who are at higher risk to develop severe infections. Our results highlight that temperature plays a key role in shaping WNV outbreak magnitude in Serbia, confirming the association between spring climatic conditions and WNV human transmission risk and thus pointing out the importance of this factor as a potential early warning predictor for timely application of preventive and control measures.

Chikungunya seroprevalence, force of infection, and prevalence of chronic disability after infection in endemic and epidemic settings: a systematic review, meta-analysis, and modelling study

Chikungunya is an arboviral disease transmitted by Aedes aegypti and Aedes albopictus mosquitoes with a growing global burden linked to climate change and globalisation. We aimed to estimate chikungunya seroprevalence, force of infection (FOI), and prevalence of related chronic disability and hospital admissions in endemic and epidemic settings. In this systematic review, meta-analysis, and modelling study, we searched PubMed, Ovid, and Web of Science for articles published from database inception until Sept 26, 2022, for prospective and retrospective cross-sectional studies that addressed serological chikungunya virus infection in any geographical region, age group, and population subgroup and for longitudinal prospective and retrospective cohort studies with data on chronic chikungunya or hospital admissions in people with chikungunya. We did a systematic review of studies on chikungunya seroprevalence and fitted catalytic models to each survey to estimate location-specific FOI (ie, the rate at which susceptible individuals acquire chikungunya infection). We performed a meta-analysis to estimate the proportion of symptomatic patients with laboratory-confirmed chikungunya who had chronic chikungunya or were admitted to hospital following infection. We used a random-effects model to assess the relationship between chronic sequelae and follow-up length using linear regression. The systematic review protocol is registered online on PROSPERO, CRD42022363102. We identified 60 studies with data on seroprevalence and chronic chikungunya symptoms done across 76 locations in 38 countries, and classified 17 (22%) of 76 locations as endemic settings and 59 (78%) as epidemic settings. The global long-term median annual FOI was 0·007 (95% uncertainty interval [UI] 0·003-0·010) and varied from 0·0001 (0·00004-0·0002) to 0·113 (0·07-0·20). The highest estimated median seroprevalence at age 10 years was in south Asia (8·0% [95% UI 6·5-9·6]), followed by Latin America and the Caribbean (7·8% [4·9-14·6]), whereas median seroprevalence was lowest in the Middle East (1·0% [0·5-1·9]). We estimated that 51% (95% CI 45-58) of people with laboratory-confirmed symptomatic chikungunya had chronic disability after infection and 4% (3-5) were admitted to hospital following infection. We inferred subnational heterogeneity in long-term average annual FOI and transmission dynamics and identified both endemic and epidemic settings across different countries. Brazil, Ethiopia, Malaysia, and India included both endemic and epidemic settings. Long-term average annual FOI was higher in epidemic settings than endemic settings. However, long-term cumulative incidence of chikungunya can be similar between large outbreaks in epidemic settings with a high FOI and endemic settings with a relatively low FOI. International Vaccine Institute.

Human Trypanosoma cruzi infection in the Argentinean Chaco: risk factors and identification of households with infected children for treatment

BackgroundChagas disease is a neglected tropical disease (NTD). Cost-effective strategies for large-scale implementation of diagnosis and etiological treatment are urgently needed to comply with NTD control goals. We determined the seroprevalence of Trypanosoma cruzi infection and associated risk factors in a well-defined rural population of Pampa del Indio municipality including creole and indigenous (Qom) households and developed two indices to identify houses harboring infected children.MethodsWe serodiagnosed and administered a questionnaire to 1337 residents (48.2% of the listed population) in two sections of the municipality (named Areas II and IV) 6–9 years after deploying sustained vector control interventions. Multiple logistic regression models were used to evaluate the relationship between human infection and a priori selected predictors. Two risk indices were constructed based on environmental and serostatus variables, and we used spatial analysis to test whether households harboring T. cruzi-seropositive children were randomly distributed.ResultsThe global seroprevalence of T. cruzi infection was 24.8%. Human infection was positively and significantly associated with exposure time to triatomines, the household number of seropositive co-inhabitants, maternal seropositivity for T. cruzi, recent residence at the current house and the presence of suitable walls for triatomine colonization in the domicile. The pre-intervention mean annual force of infection (FOI) was 1.23 per 100 person-years. Creoles from Area IV exhibited the highest seroprevalence and FOI; Qom people from both areas displayed intermediate ones and creoles from Area II the lowest. Three hotspots of infected children were spatially associated with hotspots of triatomine abundance at baseline and persistent house infestation. No child born after vector control interventions was T. cruzi seropositive except for one putative transplacental case. Two simple risk indices (based on self-reported inhabiting an infested house and suitable walls for triatomines or maternal serostatus) identified 97.3–98.6% of the households with at least one T. cruzi-seropositive child.ConclusionsWe showed strong heterogeneity in the seroprevalence of T. cruzi infection within and between ethnic groups inhabiting neighboring rural areas. Developed indices can be used for household risk stratification and to improve access of rural residents to serodiagnosis and treatment and may be easily transferred to primary healthcare personnel.Graphical

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

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. 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. 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. 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. World Health Organization.

A simulation-based method to inform serosurvey design for estimating the force of infection using existing blood samples.

The extent to which dengue virus has been circulating globally and especially in Africa is largely unknown. Testing available blood samples from previous cross-sectional serological surveys offers a convenient strategy to investigate past dengue infections, as such serosurveys provide the ideal data to reconstruct the age-dependent immunity profile of the population and to estimate the average per-capita annual risk of infection: the force of infection (FOI), which is a fundamental measure of transmission intensity. In this study, we present a novel methodological approach to inform the size and age distribution of blood samples to test when samples are acquired from previous surveys. The method was used to inform SERODEN, a dengue seroprevalence survey which is currently being conducted in Ghana among other countries utilizing samples previously collected for a SARS-CoV-2 serosurvey. The method described in this paper can be employed to determine sample sizes and testing strategies for different diseases and transmission settings.

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'.

Singapore's 5 decades of dengue prevention and control-Implications for global dengue control.

This paper summarises the lessons learnt in dengue epidemiology, risk factors, and prevention in Singapore over the last half a century, during which Singapore evolved from a city of 1.9 million people to a highly urban globalised city-state with a population of 5.6 million. Set in a tropical climate, urbanisation among green foliage has created ideal conditions for the proliferation of Aedes aegypti and Aedes albopictus, the mosquito vectors that transmit dengue. A vector control programme, largely for malaria, was initiated as early as 1921, but it was only in 1966 that the Vector Control Unit (VCU) was established to additionally tackle dengue haemorrhagic fever (DHF) that was first documented in the 1960s. Centred on source reduction and public education, and based on research into the bionomics and ecology of the vectors, the programme successfully reduced the Aedes House Index (HI) from 48% in 1966 to <5% in the 1970s. Further enhancement of the programme, including through legislation, suppressed the Aedes HI to around 1% from the 1990s. The current programme is characterised by 4 key features: (i) proactive inter-epidemic surveillance and control that is stepped up during outbreaks; (ii) risk-based prevention and intervention strategies based on advanced data analytics; (iii) coordinated inter-sectoral cooperation between the public, private, and people sectors; and (iv) evidence-based adoption of new tools and strategies. Dengue seroprevalence and force of infection (FOI) among residents have substantially and continuously declined over the 5 decades. This is consistent with the observation that dengue incidence has been delayed to adulthood, with severity highest among the elderly. Paradoxically, the number of reported dengue cases and outbreaks has increased since the 1990s with record-breaking epidemics. We propose that Singapore's increased vulnerability to outbreaks is due to low levels of immunity in the population, constant introduction of new viral variants, expanding urban centres, and increasing human density. The growing magnitude of reported outbreaks could also be attributed to improved diagnostics and surveillance, which at least partially explains the discord between rising trend in cases and the continuous reduction in dengue seroprevalence. Changing global and local landscapes, including climate change, increasing urbanisation and global physical connectivity are expected to make dengue control even more challenging. The adoption of new vector surveillance and control tools, such as the Gravitrap and Wolbachia technology, is important to impede the growing threat of dengue and other Aedes-borne diseases.

Age-dependent risk of respiratory syncytial virus infection: A systematic review and hazard modeling from serological data.

There is no immunization campaign that currently exist for respiratory syncytial virus (RSV). Seroprevalence studies are critical for assessing epidemiological dynamics before and during an immunization program. A systematic literature review was conducted to summarize the evidence from seroprevalence studies on RSV. A systematic search of age-dependent RSV seroprevalence was conducted using the PubMed database and EMBASE. Age-dependent force of infections (FoI) and the decay rate of immunity were estimated. A mixture finite model was employed, estimating the age-dependent disease state and the antibody concentrations in susceptible and infected/recovered populations. Twenty-one studies were identified from 15 countries, with studies using ELISA being the most represented. Employing a catalytic model, the age-dependent force of infection was estimated to be the lowest in infants aged 6 months to 1 year and increased in older age groups. The proportion ever-infected/recovered was estimated to be above 90% by 3 years of age. The number of seroprevalence studies covering a broad range of ages are limited. The age-dependent FoI indicated that the risk of infection was greatest among those aged >5 years. Additional empirical data that use valid assays are required to fully describe the transmission dynamics of RSV infection.

The Transmission Dynamics of a Compartmental Epidemic Model for COVID-19 with the Asymptomatic Population via Closed-Form Solutions.

Unlike previous viral diseases, COVID-19 has an "asymptomatic" group that has no symptoms but can still spread the disease to others at the same rate as symptomatic patients who are infected. In the literature, the mass action or standard incidence rates are considered for compartmental models with asymptomatic compartment for studying the transmission dynamics of COVID-19, but the quarantined adjusted incidence rate is not. To bridge this gap, we developed a Susceptible Asymptomatic Infectious Quarantined (SAIQ) model with a Quarantine-Adjusted (QA) incidence to investigate the emergence and containment of COVID-19. COVID-19 models are investigated using various methods, but only a few studies take into account closed-form solutions. The knowledge of closed-form solutions simplifies the construction of the various epidemic indicators that describe the epidemic phenomenon and makes the sensitivity analysis to variations in the data under consideration possible. The closed-form solutions of the systems of four nonlinear first-order ordinary differential equations (ODEs) are established. The Epidemic Peak (EP), Force of Infection (FOI) and Rate of Infection (ROI) are the important indicators for the control and prevention of disease. We examined these indicators using closed-form solutions and particular parameter values. Different disease control scenarios are thoroughly examined. The four scenarios to analyze COVID-19 propagation and containment are (i) lockdown, (ii) quarantine and other preventative measures, (iii) stabilizing the basic reproduction rate to a level where the pandemic can be contained and (iv) containing the epidemic through an appropriate combination of lockdown, quarantine and other preventative measures.

Modelling longitudinal binary outcomes with outcome dependent observation times: an application to a malaria cohort study

BACKGROUND: In spite of the global reduction of 21% in malaria incidence between 2010 and 2015, the disease still threatens many lives of children and pregnant mothers in African countries. A correct assessment and evaluation of the impact of malaria control strategies still remains quintessential in order to eliminate the disease and its burden. Malaria follow-up studies typically involve routine visits at pre-scheduled time points and/or clinical visits whenever individuals experience malaria-like symptoms. In the latter case, infection triggers outcome assessment, thereby leading to outcome-dependent sampling (ODS). Commonly used methods to analyze such longitudinal data ignore ODS and potentially lead to biased estimates of malaria-specific transmission parameters, hence, inducing an incorrect assessment and evaluation of malaria control strategies. METHODS: In this paper, a new method is proposed to handle ODS by use of a joint model for the longitudinal binary outcome measured at routine visits and the clinical event times. The methodology is applied to malaria parasitaemia data from a cohort of [Formula: see text] Ugandan children aged 0.5-10 years from 3 regions (Walukuba-300 children, Kihihi-355 children and Nagongera-333 children) with varying transmission intensities (entomological inoculation rate equal to 2.8, 32 and 310 infectious bites per unit year, respectively) collected between 2011-2014. RESULTS: The results indicate that malaria parasite prevalence and force of infection (FOI) increase with age in the region of high malaria intensity with highest FOI in age group 5-10 years. For the region of medium intensity, the prevalence slightly increases with age and the FOI for the routine process is highest in age group 5-10 years, yet for the clinical infections, the FOI gradually decreases with increasing age. For the region with low intensity, both the prevalence and FOI peak at the age of 1 year after which the former remains constant with age yet the latter suddenly decreases with age for the clinically observed infections. CONCLUSION: Malaria parasite prevalence and FOI increase with age in the region of high malaria intensity. In all study sites, both the prevalence and FOI are highest among previously asymptomatic children and lowest among their symptomatic counterparts. Using a simulation study inspired by the malaria data at hand, the proposed methodology shows to have the smallest bias, especially when consecutive positive malaria parasitaemia presence results within a time period of 35 days were considered to be due to the same infection.

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

BackgroundHand, 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. MethodsWe 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. Results4,096,270 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. ConclusionMore 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.

Modelling the West Nile virus force of infection in the European human population

West Nile virus (WNV) is among the most recent emerging mosquito-borne pathogens in Europe where each year hundreds of human cases are recorded. We developed a relatively simple technique to model the WNV force of infection (FOI) in the human population to assess its dependence on environmental and human demographic factors. To this aim, we collated WNV human case-based data reported to the European Surveillance System from 15 European Countries during the period 2010–2021. We modelled the regional WNV FOI for each year through normal distributions and calibrated the constituent parameters, namely average (peak timing), variance and overall intensity, to observed cases. Finally, we investigated through regression models how these parameters are associated to a set of climatic, environmental and human demographic covariates. Our modelling approach shows good agreement between expected and observed epidemiological curves. We found that FOI magnitude is positively associated with spring temperature and larger in more anthropogenic semi-natural areas, while FOI peak timing is negatively related to summer temperature. Unsurprisingly, FOI is estimated to be greater in regions with a larger fraction of elderly people, who are more likely to contract severe infections. Our results confirm that temperature plays a key role in shaping WNV transmission in Europe and provide some interesting hints on how human presence and demography might affect WNV burden. This simple yet reliable approach could be easily adopted for early warning and to address epidemiological investigations of other vector-borne diseases, especially where eco-epidemiological data are scarce.

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.

Inter-epidemic Rift Valley fever virus infection incidence and risks for zoonotic spillover in northern Tanzania.

Rift Valley fever virus (RVFV) is a mosquito-borne pathogen that has caused epidemics involving people and animals across Africa and the Arabian Peninsula. A number of studies have found evidence for the circulation of RVFV among livestock between these epidemics but the population-level incidence of infection during this inter-epidemic period (IEP) is rarely reported. General force of infection (FOI) models were applied to age-adjusted cross-sectional serological data to reconstruct the annual FOI and population-level incidence of RVFV infection among cattle, goats, and sheep in northern Tanzania from 2009 through 2015, a period without reported Rift Valley fever (RVF) cases in people or animals. To evaluate the potential for zoonotic RVFV spillover during this period, the relationship between village-level livestock RVFV FOI and human RVFV seropositivity was quantified using multi-level logistic regression. The predicted average annual incidence was 72 (95% Credible Interval [CrI] 63, 81) RVFV infections per 10,000 animals and 96 (95% CrI 81, 113), 79 (95% CrI 62, 98), and 39 (95% CrI 28, 52) per 10,000 cattle, sheep, and goats, respectively. There was variation in transmission intensity between study villages, with the highest estimated village-level FOI 2.49% (95% CrI 1.89, 3.23) and the lowest 0.12% (95% CrI 0.02, 0.43). The human RVFV seroprevalence was 8.2% (95% Confidence Interval 6.2, 10.9). Human seropositivity was strongly associated with the village-level FOI in livestock, with the odds of seropositivity in an individual person increasing by around 1.2 times (95% CrI 1.1, 1.3) for each additional annual RVFV seroconversion per 1,000 animals. A history of raw milk consumption was also positively associated with human seropositivity. RVFV has circulated at apparently low levels among livestock in northern Tanzania in the period since the last reported epidemic. Although our data do not allow us to confirm human RVFV infections during the IEP, a strong association between human seropositivity and the FOI in cattle, goats, and sheep supports the hypothesis that RVFV circulation among livestock during the IEP poses a risk for undetected zoonotic spillover in northern Tanzania. We provide further evidence for the likely role of raw milk consumption in RVFV transmission from animals to people.

Global variation in force-of-infection trends for human Taenia solium taeniasis/cysticercosis

Infection by Taenia solium poses a major burden across endemic countries. The World Health Organization (WHO) 2021-2030 Neglected Tropical Diseases roadmap has proposed that 30% of endemic countries achieve intensified T. solium control in hyperendemic areas by 2030. Understanding geographical variation in age-prevalence profiles and force-of-infection (FoI) estimates will inform intervention designs across settings. Human taeniasis (HTT) and human cysticercosis (HCC) age-prevalence data from 16 studies in Latin America, Africa, and Asia were extracted through a systematic review. Catalytic models, incorporating diagnostic performance uncertainty, were fitted to the data using Bayesian methods, to estimate rates of antibody (Ab)-seroconversion, infection acquisition and Ab-seroreversion or infection loss. HCC FoI and Ab-seroreversion rates were also estimated across 23 departments in Colombia from 28,100 individuals. Across settings, there was extensive variation in all-ages seroprevalence. Evidence for Ab-seroreversion or infection loss was found in most settings for both HTT and HCC and for HCC Ab-seroreversion in Colombia. The average duration until humans became Ab-seropositive/infected decreased as all-age (sero)prevalence increased. There was no clear relationship between the average duration humans remain Ab-seropositive and all-age seroprevalence. Marked geographical heterogeneity in T. solium transmission rates indicate the need for setting-specific intervention strategies to achieve the WHO goals.

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, pvalue=.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.

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.

Linear and Machine Learning modelling for spatiotemporal disease predictions: Force-of-Infection of Chagas disease.

Chagas disease is a long-lasting disease with a prolonged asymptomatic period. Cumulative indices of infection such as prevalence do not shed light on the current epidemiological situation, as they integrate infection over long periods. Instead, metrics such as the Force-of-Infection (FoI) provide information about the rate at which susceptible people become infected and permit sharper inference about temporal changes in infection rates. FoI is estimated by fitting (catalytic) models to available age-stratified serological (ground-truth) data. Predictive FoI modelling frameworks are then used to understand spatial and temporal trends indicative of heterogeneity in transmission and changes effected by control interventions. Ideally, these frameworks should be able to propagate uncertainty and handle spatiotemporal issues. We compare three methods in their ability to propagate uncertainty and provide reliable estimates of FoI for Chagas disease in Colombia as a case study: two Machine Learning (ML) methods (Boosted Regression Trees (BRT) and Random Forest (RF)), and a Linear Model (LM) framework that we had developed previously. Our analyses show consistent results between the three modelling methods under scrutiny. The predictors (explanatory variables) selected, as well as the location of the most uncertain FoI values, were coherent across frameworks. RF was faster than BRT and LM, and provided estimates with fewer extreme values when extrapolating to areas where no ground-truth data were available. However, BRT and RF were less efficient at propagating uncertainty. The choice of FoI predictive models will depend on the objectives of the analysis. ML methods will help characterise the mean behaviour of the estimates, while LM will provide insight into the uncertainty surrounding such estimates. Our approach can be extended to the modelling of FoI patterns in other Chagas disease-endemic countries and to other infectious diseases for which serosurveys are regularly conducted for surveillance.