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Background Great progress is being made toward the goal of elimination as a public health problem for neglected tropical diseases such as leprosy, human African trypanosomiasis, Buruli ulcer, and visceral leishmaniasis, which relies on intensified disease management and case finding. However, strategies for maintaining this goal are still under discussion. Passive surveillance is a core pillar of a long-term, sustainable surveillance program. Methods We use a generic model of disease transmission with slow epidemic growth rates and cases detected through severe symptoms and passive detection to evaluate under what circumstances passive detection alone can keep transmission under control. Results Reducing the period of infectiousness due to decreasing time to treatment has a small effect on reducing transmission. Therefore, to prevent resurgence, passive surveillance needs to be very efficient. For some diseases, the treatment time and level of passive detection needed to prevent resurgence is unlikely to be obtainable. Conclusions The success of a passive surveillance program crucially depends on what proportion of cases are detected, how much of their infectious period is reduced, and the underlying reproduction number of the disease. Modeling suggests that relying on passive detection alone is unlikely to be enough to maintain elimination goals. [ABSTRACT FROM AUTHOR]

Background: Effective case identification strategies are fundamental to capturing the remaining visceral leishmaniasis (VL) cases in India. To inform government strategies to reach and sustain elimination benchmarks, this study presents costs of active- and passive- case detection (ACD and PCD) strategies used in India's most VL-endemic state, Bihar, with a focus on programme outcomes stratified by district-level incidence. Methods: Expenditure analysis was complemented by onsite micro-costing to compare the cost of PCD in hospitals alongside index case-based ACD and a combination of blanket (house-to-house) and camp ACD from January to December 2018. From the provider's perspective, a cost analysis evaluated the overall programme cost of each activity, the cost per case detected, and the cost of scaling up ACD. Results: During 2018, index case-based ACD, blanket and camp ACD, and PCD reported 1,497, 131, and 1,983 VL-positive cases at a unit cost of $522.81, $4,186.81, and $246.79, respectively. In high endemic districts, more VL cases were identified through PCD while in meso- and low-endemic districts more cases were identified through ACD. The cost of scaling up ACD to identify 3,000 additional cases ranged from $1.6–4 million, depending on the extent to which blanket and camp ACD was relied upon. Conclusion: Cost per VL test conducted (rather than VL-positive case identified) may be a better metric estimating unit costs to scale up ACD in Bihar. As more VL cases were identified in meso-and low-endemic districts through ACD than PCD, health authorities in India should consider bolstering ACD in these areas. Blanket and camp ACD identified fewer cases at a higher unit cost than index case-based ACD. However, the value of detecting additional VL cases early outweighs long-term costs for reaching and sustaining VL elimination benchmarks in India. Author summary: Visceral leishmaniasis (VL) is targeted for elimination in India by 2020, where early identification and prompt treatment are essential measures for reaching and sustaining incidence benchmarks. Both active- and passive- case detection (ACD and PCD) strategies have been employed in recent years, and evaluating the cost and outputs of each is now important for sustaining funding and political momentum. This study presents overall and unit costs for PCD, index case-based ACD (where neighbours in the vicinity of a recent VL case are screened), and a combination of blanket and camp ACD (involving house-to-house case searching and weekly diagnostic camps) in Bihar, India during 2018. Results of this study indicate that a larger proportion of VL cases were found through PCD in high incidence districts, which may be related to increased interaction with ACD officers. ACD can be bolstered in meso- and low-incidence districts where educational exposure to VL is low and risk of resurgence is high. Although blanket and camp ACD unit costs were at least four times higher than index case-based ACD, the number of VL cases identified through this approach may warrant the investment to achieve VL elimination. Cost and outcomes of VL case finding approaches need to be continuously evaluated until elimination benchmarks are reached and integrated into sustained surveillance programmes. [ABSTRACT FROM AUTHOR]

Recent mathematical and statistical modeling of leprosy incidence data provides estimates of the current undiagnosed population and projections of diagnosed cases, as well as ongoing transmission. Furthermore, modeling studies have been used to evaluate the effectiveness of proposed intervention strategies, such as postleprosy exposure prophylaxis and novel diagnostics, relative to current approaches. Such modeling studies have revealed both a slow decline of new cases and a substantial pool of undiagnosed infections. These findings highlight the need for active case detection, particularly targeting leprosy foci, as well as for continued research into innovative accurate, rapid, and cost-effective diagnostics. As leprosy incidence continues to decline, targeted active case detection primarily in foci and connected areas will likely become increasingly important. [ABSTRACT FROM AUTHOR]

Background: The number of new leprosy cases reported annually is falling worldwide, but remains relatively high in some populations. Because of the long and variable periods between infection, onset of disease, and diagnosis, the recently detected cases are a reflection of infection many years earlier. Estimation of the numbers of sub-clinical and clinical infections would be useful for management of elimination programmes. Back-calculation is a methodology that could provide estimates of prevalence of undiagnosed infections, future diagnoses and the effectiveness of control. Methods: A basic back-calculation model to investigate the infection dynamics of leprosy has been developed using Markov Chain Monte Carlo in a Bayesian context. The incidence of infection and the detection delay both vary with calendar time. Public data from Thailand are used to demonstrate the results that are obtained as the incidence of diagnosed cases falls. Results: The results show that the underlying burden of infection and short-term future predictions of cases can be estimated with a simple model. The downward trend in new leprosy cases in Thailand is expected to continue. In 2015 the predicted total number of undiagnosed sub-clinical and clinical infections is 1,168 (846-1,546) of which 466 (381-563) are expected to be clinical infections. Conclusions: Bayesian back-calculation has great potential to provide estimates of numbers of individuals in health/ infection states that are as yet unobserved. Predictions of future cases provides a quantitative measure of understanding for programme managers and evaluators. We will continue to develop the approach, and suggest that it might be useful for other NTD in which incidence of diagnosis is not an immediate measure of infection. [ABSTRACT FROM AUTHOR]

Several countries have come close to eliminating leprosy, but leprosy cases continue to be detected at low levels. Due to the long, highly variable delay from infection to detection, the relationship between observed cases and transmission is uncertain. The World Health Organization's new technical guidance provides a path for countries to reach elimination. We use a simple probabilistic model to simulate the stochastic dynamics of detected cases as transmission declines, and evaluate progress through the new public health milestones. In simulations where transmission is halted, 5 years of zero incidence in autochthonous children, combined with 3 years of zero incidence in all ages is a flawed indicator that transmission has halted (54% correctly classified). A further 10 years of only occasional sporadic cases is associated with a high probability of having interrupted transmission (99%). If, however, transmission continues at extremely low levels, it is possible that cases could be misidentified as historic cases from the tail of the incubation period distribution, although misleadingly achieving all three milestones is unlikely (less than 1% probability across a 15-year period of ongoing low-level transmission). These results demonstrate the feasibility and challenges of a phased progression of milestones towards interruption of transmission, allowing assessment of programme status. 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'. [ABSTRACT FROM AUTHOR]

Epidemics, such as HIV in the early 1980s and Ebola in 2014, inspire decisive government investment and action, and individual and societal concern, sometimes bordering on panic. By contrast, endemic diseases, such as HIV in 2017 and tuberculosis, struggle to maintain the same attention. For many, the paradox is that endemic disease, in its totality, continues to impose a far higher public health burden than epidemic disease. Overall, the swift political response to epidemics has resulted in success. It has proven possible to eradicate epidemic diseases, often without the availability of vaccines and other biomedical technologies. In recent times, only HIV has made the transition from epidemic to endemic, but diseases that have existed for centuries continue to cause most of the infectious disease burden. [ABSTRACT FROM AUTHOR]

Background: The HIV epidemic remains a major public health problem. Critical to transmission control are HIV prevention strategies with new interventions continuing to be developed. Mathematical models are important for understanding the potential impact of these interventions and supporting policy decisions. This systematic review aims to answer the following question: when a new HIV prevention intervention is being considered or designed, what information regarding it is necessary to include in a compartmental model to provide useful insights to policy makers? The primary objective of this review is therefore to assess suitability of current compartmental HIV prevention models for informing policy development. Methods: Articles published in EMBASE, Medline, Econlit, and Global Health were screened. Included studies were identified using permutations of (i) HIV, (ii) pre-exposure prophylaxis (PrEP), circumcision (both voluntary male circumcision [VMMC] and early-infant male circumcision [EIMC]), and vaccination, and (iii) modelling. Data extraction focused on study design, model structure, and intervention incorporation into models. Article quality was assessed using the TRACE (TRAnsparent and Comprehensive Ecological modelling documentation) criteria for mathematical models. Results: Of 837 articles screened, 48 articles were included in the review, with 32 unique mathematical models identified. The substantial majority of studies included PrEP (83%), whilst fewer modelled circumcision (54%), and only a few focussed on vaccination (10%). Data evaluation, implementation verification, and model output corroboration were identified as areas of poorer model quality. Parameters commonly included in the mathematical models were intervention uptake and effectiveness, with additional intervention-specific common parameters identified. We identified key modelling gaps; critically, models insufficiently incorporate multiple interventions acting simultaneously. Additionally, population subgroups were generally poorly represented—with future models requiring improved incorporation of ethnicity and sexual risk group stratification—and many models contained inappropriate data in parameterisation which will affect output accuracy. Conclusions: This review identified gaps in compartmental models to date and suggests areas of improvement for models focusing on new prevention interventions. Resolution of such gaps within future models will ensure greater robustness and transparency, and enable more accurate assessment of the impact that new interventions may have, thereby providing more meaningful guidance to policy makers. [ABSTRACT FROM AUTHOR]

In this article, the author focuses on a research related to Leprosy which is considered as a public health problem. It mentions need for data to drive the politics in public health and not the politics drive the data, and need for data to be uncompromised. It also mentions the effort and effectiveness of case finding also impact on the delays which patients experience between infection, onset of disease, diagnosis and cure.

Background: Bovine herpesvirus type-1 (BHV-1) is an important pathogen of cattle that presents with a variety of clinical signs, including the upper respiratory tract infection infectious bovine rhinotracheitis (IBR). A seroepidemiological study of BHV-1 antibodies was conducted in England from 2002 - 2004: 29,782 blood samples were taken from 15,736 cattle from 114 herds which were visited on up to three occasions. Antibody concentration was measured using a commercial ELISA. Farm management information was collected using an interview questionnaire, and herd size and cattle movements were obtained from the cattle tuberculosis testing database and the British Cattle Movement Service. Hierarchical statistical models were used to investigate associations between cattle and herd variables and the continuous outcome percentage positive (PP) values from the ELISA test in unvaccinated herds. Results: There were 7 vaccinated herds, all with at least one seropositive bovine. In unvaccinated herds 83.2% had at least one BHV-1 seropositive bovine, and the mean cattle and herd BHV-1 seroprevalence were 42.5% and 43.1% respectively. There were positive associations between PP value, age, herd size, presence of dairy cattle. Adult cattle in herds with grower cattle had lower PP values than those in herds without grower cattle. Purchased cattle had significantly lower PP values than homebred cattle, whereas cattle in herds that were totally restocked after the foot-and-mouth epidemic in 2001 had significantly higher PP values than those in continuously stocked herds. Samples taken in spring and summer had significantly lower PP values than those taken in winter, whereas those taken in autumn had significantly higher PP values than those taken in winter. The risks estimated from a logistic regression model with a binary outcome (seropositive yes/no) were similar. Conclusion: The prevalence of BHV-1 seropositivity in cattle and herds has increased since the 1970s. Although the study population prevalence of BHV-1 was temporally stable during study period, the associations between serological status and cattle age, herd size, herd type, presence of young stock and restocked versus continuously stocked herds indicate that there is heterogeneity between herds and so potential for further spread of BHV-1 within and between herds. [ABSTRACT FROM AUTHOR]

Background: Neosporosis caused by the protozoan parasite Neospora caninum, is an economically important cause of abortion, stillbirth, low milk yield, reduced weight gain and premature culling in cattle. Consequently, a seroepidemiological study of N. caninum antibodies was conducted in England with 29,782 samples of blood taken from 15,736 cattle from 114 herds visited on three occasions at yearly intervals. Herds were categorised into lower (< 10%) and higher (≥ 10%) median herd seroprevalence. Hierarchical models were run to investigate associations between the sample to positive (S/P) ratio and herd and cattle factors. Results: Ninety-four percent of herds had at least one seropositive cow; 12.9% of adult cattle had at least one seropositive test. Approximately 90% of herds were seropositive at all visits; 9 herds (8%) changed serological status between visits. The median N. caninum seroprevalence in positive herds was 10% (range 0.4% to 58.8%). There was a positive association between the serostatus of offspring and dams that were ever seropositive. In the hierarchical model of low seroprevalence herds there was no significant association between S/P ratio and cattle age. There was a significantly lower S/P ratio in cattle in herds that were totally restocked after the foot-and-mouth epidemic of 2001 compared with those from continuously stocked herds and cattle purchased into these herds had a higher S/P ratio than homebred cattle. In the model of high seroprevalence herds the S/P ratio increased with cattle age, but was not associated with restocking or cattle origin. Conclusion: There were no strong temporal changes in herd seroprevalence of N. caninum but 90% of herds had some seropositive cattle over this time period. Vertical transmission from seropositive dams appeared to occur in all herds. In herds with a high seroprevalence the increasing S/P ratio in 2-4 year old cattle is suggestive of exposure to N. caninum: horizontal transmission between adult cattle, infection from a local source or recrudescence and abortions. Between-herd movements of infected cattle enhance the spread of N. caninum, particularly into low seroprevalence herds. Some restocked herds had little exposure to N. caninum, while in others infection had spread in the time since restocking. [ABSTRACT FROM AUTHOR]

Hepatitis-B virus infection is globally ubiquitous, but its distribution is very heterogeneous, with prevalence of serological markers in various nations ranging from less than 1% to more than 90%. We propose an explanation for this diversity using a mathematical model of hepatitis-B virus transmission dynamics that shows, for the first time, 'catastrophic' behavior using realistic epidemiological processes and parameters. Our major conclusion is that the prevalence of infection is largely determined by a feedback mechanism that relates the rate of transmission, average age at infection and age-related probability of developing carriage following infection. Using the model we identify possible, highly non-linear, consequences of chemotherapy and immunization interventions, for which the starting prevalence of carriers is the most influential, predictive quantity. Taken together, our results demand a re-evaluation of public health policy towards hepatitis-B. [ABSTRACT FROM AUTHOR]

Background The Global Programme to Eliminate Lymphatic Filariasis (GPELF) aims to reduce and maintain infection levels through mass drug administration (MDA), but there is evidence of ongoing transmission after MDA in areas where Culex mosquitoes are the main transmission vector, suggesting that a more stringent criterion is required for MDA decision making in these settings. Methods We use a transmission model to investigate how a lower prevalence threshold (<1% antigenemia [Ag] prevalence compared with <2% Ag prevalence) for MDA decision making would affect the probability of local elimination, health outcomes, the number of MDA rounds, including restarts, and program costs associated with MDA and surveys across different scenarios. To determine the cost-effectiveness of switching to a lower threshold, we simulated 65% and 80% MDA coverage of the total population for different willingness to pay per disability-adjusted life-year averted for India ($446.07), Tanzania ($389.83), and Haiti ($219.84). Results Our results suggest that with a lower Ag threshold, there is a small proportion of simulations where extra rounds are required to reach the target, but this also reduces the need to restart MDA later in the program. For 80% coverage, the lower threshold is cost-effective across all baseline prevalences for India, Tanzania, and Haiti. For 65% MDA coverage, the lower threshold is not cost-effective due to additional MDA rounds, although it increases the probability of local elimination. Valuing the benefits of elimination to align with the GPELF goals, we find that a willingness to pay per capita government expenditure of approximately $1000–$4000 for 1% increase in the probability of local elimination would be required to make a lower threshold cost-effective. Conclusions Lower Ag thresholds for stopping MDAs generally mean a higher probability of local elimination, reducing long-term costs and health impacts. However, they may also lead to an increased number of MDA rounds required to reach the lower threshold and, therefore, increased short-term costs. Collectively, our analyses highlight that lower target Ag thresholds have the potential to assist programs in achieving lymphatic filariasis goals. [ABSTRACT FROM AUTHOR]

Background Control of schistosomiasis (SCH) relies on the regular distribution of preventive chemotherapy (PC) over many years. For the sake of sustainable SCH control, a decision must be made at some stage to scale down or stop PC. These "stopping decisions" are based on population surveys that assess whether infection levels are sufficiently low. However, the limited sensitivity of the currently used diagnostic (Kato-Katz [KK]) to detect low-intensity infections is a concern. Therefore, the use of new, more sensitive, molecular diagnostics has been proposed. Methods Through statistical analysis of Schistosoma mansoni egg counts collected from Burundi and a simulation study using an established transmission model for schistosomiasis, we investigated the extent to which more sensitive diagnostics can improve decision making regarding stopping or continuing PC for the control of S. mansoni. Results We found that KK-based strategies perform reasonably well for determining when to stop PC at a local scale. Use of more sensitive diagnostics leads to a marginally improved health impact (person-years lived with heavy infection) and comes at a cost of continuing PC for longer (up to around 3 years), unless the decision threshold for stopping PC is adapted upward. However, if this threshold is set too high, PC may be stopped prematurely, resulting in a rebound of infection levels and disease burden (+45% person-years of heavy infection). Conclusions We conclude that the potential value of more sensitive diagnostics lies more in the reduction of survey-related costs than in the direct health impact of improved parasite control. [ABSTRACT FROM AUTHOR]

Retrospective analyses of the non-pharmaceutical interventions (NPIs) used to combat the ongoing COVID-19 outbreak have highlighted the potential of optimizing interventions. These optimal interventions allow policymakers to manage NPIs to minimize the epidemiological and human health impacts of both COVID-19 and the intervention itself. Here, we use a susceptible-infectious-recovered (SIR) mathematical model to explore the feasibility of optimizing the duration, magnitude and trigger point of five different NPI scenarios to minimize the peak prevalence or the attack rate of a simulated UK COVID-19 outbreak. An optimal parameter space to minimize the peak prevalence or the attack rate was identified for each intervention scenario, with each scenario differing with regard to how reductions to transmission were modelled. However, we show that these optimal interventions are fragile, sensitive to epidemiological uncertainty and prone to implementation error. We highlight the use of robust, but suboptimal interventions as an alternative, with these interventions capable of mitigating the peak prevalence or the attack rate over a broader, more achievable parameter space, but being less efficacious than theoretically optimal interventions. This work provides an illustrative example of the concept of intervention optimization across a range of different NPI strategies. [ABSTRACT FROM AUTHOR]

As programs move closer toward the World Health Organization (WHO) goals of reduction in morbidity, elimination as a public health problem or elimination of transmission, countries will be faced with planning the next stages of surveillance and control in low prevalence settings. Mathematical models of neglected tropical diseases (NTDs) will need to go beyond predicting the effect of different treatment programs on these goals and on to predicting whether the gains can be sustained. One of the most important challenges will be identifying the policy goal and the right constraints on interventions and surveillance over the long term, as a single policy option will not achieve all aims—for example, minimizing morbidity and minimizing costs cannot both be achieved. As NTDs move toward 2030 and beyond, more nuanced intervention choices will be informed by quantitative analyses which are adapted to national context. [ABSTRACT FROM AUTHOR]

Background: As of 2021, the National Kala-azar Elimination Programme (NKAEP) in India has achieved visceral leishmaniasis (VL) elimination (<1 case / 10,000 population/year per block) in 625 of the 633 endemic blocks (subdistricts) in four states. The programme needs to sustain this achievement and target interventions in the remaining blocks to achieve the WHO 2030 target of VL elimination as a public health problem. An effective tool to analyse programme data and predict/ forecast the spatial and temporal trends of VL incidence, elimination threshold, and risk of resurgence will be of use to the programme management at this juncture. Methodology/principal findings: We employed spatiotemporal models incorporating environment, climatic and demographic factors as covariates to describe monthly VL cases for 8-years (2013–2020) in 491 and 27 endemic and non-endemic blocks of Bihar and Jharkhand states. We fitted 37 models of spatial, temporal, and spatiotemporal interaction random effects with covariates to monthly VL cases for 6-years (2013–2018, training data) using Bayesian inference via Integrated Nested Laplace Approximation (INLA) approach. The best-fitting model was selected based on deviance information criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC) and was validated with monthly cases for 2019–2020 (test data). The model could describe observed spatial and temporal patterns of VL incidence in the two states with widely differing incidence trajectories, with >93% and 99% coverage probability (proportion of observations falling inside 95% Bayesian credible interval for the predicted number of VL cases per month) during the training and testing periods. PIT (probability integral transform) histograms confirmed consistency between prediction and observation for the test period. Forecasting for 2021–2023 showed that the annual VL incidence is likely to exceed elimination threshold in 16–18 blocks in 4 districts of Jharkhand and 33–38 blocks in 10 districts of Bihar. The risk of VL in non-endemic neighbouring blocks of both Bihar and Jharkhand are less than 0.5 during the training and test periods, and for 2021–2023, the probability that the risk greater than 1 is negligible (P<0.1). Fitted model showed that VL occurrence was positively associated with mean temperature, minimum temperature, enhanced vegetation index, precipitation, and isothermality, and negatively with maximum temperature, land surface temperature, soil moisture and population density. Conclusions/significance: The spatiotemporal model incorporating environmental, bioclimatic, and demographic factors demonstrated that the KAMIS database of the national programmme can be used for block level predictions of long-term spatial and temporal trends in VL incidence and risk of outbreak / resurgence in endemic and non-endemic settings. The database integrated with the modelling framework and a dashboard facility can facilitate such analysis and predictions. This could aid the programme to monitor progress of VL elimination at least one-year ahead, assess risk of resurgence or outbreak in post-elimination settings, and implement timely and targeted interventions or preventive measures so that the NKAEP meet the target of achieving elimination by 2030. Author summary: In India, VL has been endemic in four states (Bihar, Jharkhand, Uttar Pradesh, and West Bengal), having over 165 million population. The national programme achieved elimination (<1 case / 10,000 population/year per 'block') in 625 of the 633 endemic blocks in 2021. While sustaining elimination level, the programme needs to target other blocks yet to reach elimination to achieve the WHO 2030 target. We fitted a variety of spatiotemporal models to 72-monthly reported VL cases (2013–2018, training period) from 491 endemic and 27 non-endemic blocks in Bihar and Jharkhand. The best fitting model was validated with 24-month reported cases (2019–2020, test period). Model predictions agree with >93 and 99% of the monthly-observations for the periods. Forecasting for 2021–2023 showed that incidence is likely to exceed elimination threshold in 16–18 and 33–38 historically high endemic blocks of Jharkhand and Bihar. Fitted model showed that VL incidence is positively associated with mean temperature, minimum temperature, enhanced vegetation index, precipitation, and isothermality, and negatively with maximum temperature, land surface temperature, soil moisture and population density. Forecasting VL incidence at block level can aid to monitor elimination progress, target the blocks yet to reach elimination and long-term monitoring of risk of resurgence during post-elimination. [ABSTRACT FROM AUTHOR]

The author comments on the national programme to control bovine tuberculosis (TB) in Great Britain.

Background: Human papillomavirus (HPV) is the most widespread sexually transmitted infection worldwide. It causes several health consequences, in particular accounting for the majority of cervical cancer cases in women. In the United Kingdom, a vaccination campaign targeting 12-year-old girls started in 2008; this campaign has been successful, with high uptake and reduced HPV prevalence observed in vaccinated cohorts. Recently, attention has focused on vaccinating both sexes, due to HPV-related diseases in males (particularly for high-risk men who have sex with men) and an equity argument over equalising levels of protection.Methods: We constructed an epidemiological model for HPV transmission in the UK, accounting for nine of the most common HPV strains. We complemented this with an economic model to determine the likely health outcomes (healthcare costs and quality-adjusted life years) for individuals from the epidemiological model. We then tested vaccination with the three HPV vaccines currently available, vaccinating either girls alone or both sexes. For each strategy we calculated the threshold price per vaccine dose, i.e. the maximum amount paid for the added health benefits of vaccination to be worth the cost of each vaccine dose. We calculated results at 3.5% discounting, and also 1.5%, to consider the long-term health effects of HPV infection.Results: At 3.5% discounting, continuing to vaccinate girls remains highly cost-effective compared to halting vaccination, with threshold dose prices of £56-£108. Vaccination of girls and boys is less cost-effective (£25-£53). Compared to vaccinating girls only, adding boys to the programme is not cost-effective, with negative threshold prices (-£6 to -£3) due to the costs of administration. All threshold prices increase when using 1.5% discounting, and adding boys becomes cost-effective (£36-£47). These results are contingent on the UK's high vaccine uptake; for lower uptake rates, adding boys (at the same uptake rate) becomes more cost effective.Conclusions: Vaccinating girls is extremely cost-effective compared with no vaccination, vaccinating both sexes is less so. Adding boys to an already successful girls-only programme has a low cost-effectiveness, as males have high protection through herd immunity. If future health effects are weighted more heavily, threshold prices increase and vaccination becomes cost-effective. [ABSTRACT FROM AUTHOR]

Investigates the patterns of disease caused by the infectious agent responsible for bovine spongiform encephalopathy (BSE) in Great Britain. Number of variant Creutzfeldt-Jacob disease case diagnosed; Factors affecting the complication of incubation of period distribution; Importance of developing an understanding of the process of epidemics.

Background: The kala-azar elimination programme has resulted in a significant reduction in visceral leishmaniasis (VL) cases across the Indian Subcontinent. To detect any resurgence of transmission, a sensitive cost-effective surveillance system is required. Molecular xenomonitoring (MX), detection of pathogen DNA/RNA in vectors, provides a proxy of human infection in the lymphatic filariasis elimination programme. To determine whether MX can be used for VL surveillance in a low transmission setting, large numbers of the sand fly vector Phlebotomus argentipes are required. This study will determine the best method for capturing P. argentipes females for MX. Methodology/Principal findings: The field study was performed in two programmatic and two non-programmatic villages in Bihar, India. A total of 48 households (12/village) were recruited. Centers for Disease Control and Prevention light traps (CDC-LTs) were compared with Improved Prokopack (PKP) and mechanical vacuum aspirators (MVA) using standardised methods. Four 12x12 Latin squares, 576 collections, were attempted (12/house, 144/village,192/method). Molecular analyses of collections were conducted to confirm identification of P. argentipes and to detect human and Leishmania DNA. Operational factors, such as time burden, acceptance to householders and RNA preservation, were also considered. A total of 562 collections (97.7%) were completed with 6,809 sand flies captured. Females comprised 49.0% of captures, of which 1,934 (57.9%) were identified as P. argentipes. CDC-LTs collected 4.04 times more P. argentipes females than MVA and 3.62 times more than PKP (p<0.0001 for each). Of 21,735 mosquitoes in the same collections, no significant differences between collection methods were observed. CDC-LTs took less time to install and collect than to perform aspirations and their greater yield compensated for increased sorting time. No significant differences in Leishmania RNA detection and quantitation between methods were observed in experimentally infected sand flies maintained in conditions simulating field conditions. CDC-LTs were favoured by householders. Conclusions/Significance: CDC-LTs are the most useful collection tool of those tested for MX surveillance since they collected higher numbers of P. argentipes females without compromising mosquito captures or the preservation of RNA. However, capture rates are still low. Author summary: Molecular xenomonitoring, screening insects for pathogen DNA/RNA, may be used for surveillance of diseases transmitted by insects. Since the proportion of insects infected with pathogens is very low in areas targeted for disease elimination, large numbers of females need to be screened. We compared three different methods for collecting Phlebotomus argentipes sand fly females, the vector of parasites causing the disease visceral leishmaniasis in the Indian subcontinent, to determine which collected the largest number of females. Other factors that may also influence selection of a particular method of collection by a disease control programme, such as the time it takes to collect and sort samples, the acceptance of householders for a particular collection method and whether RNA degradation in insect samples differed between collection methods, were also considered. Centers for Disease Control and Prevention light traps (CDC-LTs) proved to be more useful than two types of aspiration methods for collecting higher numbers of sand fly females and RNA preservation was retained. Furthermore, they took less time to install than to perform aspirations and were favoured by householders. Therefore, CDC-LTs were considered to be the most suitable collection method for molecular xenomonitoring of sand flies in India. [ABSTRACT FROM AUTHOR]

Background: Considerable evidence on the costs and cost-effectiveness of biomedical, non-surgical interventions to prevent human immunodeficiency virus (HIV) transmission has been generated over the last decade. This study aims to synthesize findings and identify remaining knowledge gaps to suggest future research priorities. Methods: A systematic literature review was carried out in August 2020 using the MEDLINE, Embase, Global Health and EconLit databases to retrieve economic evaluations and costing studies of oral pre-exposure prophylaxis (PrEP), injectable long-acting PrEP, vaginal microbicide rings and gels, HIV vaccines and broadly neutralizing antibodies. Studies reporting costs from the provider or societal perspective were included in the analysis. Those reporting on behavioural methods of prevention, condoms and surgical approaches (voluntary medical male circumcision) were excluded. The quality of reporting of the included studies was assessed using published checklists. Results: We identified 3007 citations, of which 87 studies were retained. Most were set in low- and middle-income countries (LMICs; n = 53) and focused on the costs and/or cost-effectiveness of oral PrEP regimens (n = 70). Model-based economic evaluations were the most frequent study design; only two trial-based cost-effectiveness analyses and nine costing studies were found. Less than half of the studies provided practical details on how the intervention would be delivered by the health system, and only three of these, all in LMICs, explicitly focused on service integration and its implication for delivery costs. 'Real-world' programme delivery mechanisms and costs of intervention delivery were rarely considered. PrEP technologies were generally found to be cost-effective only when targeting high-risk subpopulations. Single-dose HIV vaccines are expected to be cost-effective for all groups despite substantial uncertainty around pricing. Conclusions: A lack of primary, detailed and updated cost data, including above-service level costs, from a variety of settings makes it difficult to evaluate the cost-effectiveness of specific delivery modes at scale, or to evaluate strategies for services integration. Closing this evidence gap around real-world implementation is vital, not least because the strategies targeting high-risk groups that are recommended by PrEP models may incur substantially higher costs and be of limited practical feasibility in some settings. [ABSTRACT FROM AUTHOR]

Respiratory syncytial virus BA genotype has reportedly replaced other group B genotypes worldwide. We report the observation of three group B viruses, all identical in G sequence but lacking the BA duplication, at a coastal district hospital in Kenya in early 2012. This follows a period of six consecutive respiratory syncytial virus ( RSV) epidemics with 100% BA dominance among group B isolates. The new strains appear only distantly related to BA variants and to previously circulating SAB1 viruses last seen in the district in 2005, suggesting that they were circulating elsewhere undetected. These results are of relevance to an understanding of RSV persistence. [ABSTRACT FROM AUTHOR]

Abstract: The incidence of herd breakdown (HBD) with bovine tuberculosis (bTB) has continued to increase year on year since the 1980s in Great Britain. The management of bTB constitutes a major challenge for government and the cattle industry. Whilst various factors have been implicated with the risk of HBD with bTB, factors involved in recovery are less well described. In this paper, we used a multilevel multistate model to identify the factors affecting the probability of a herd being placed under restriction following a bTB outbreak and the factors involved in those restrictions being lifted. By modelling both transitions within the same model, we control for unobserved herd-specific characteristics, and investigate the frequency of change between the restricted and derestricted states. There were two patterns of herd breakdown: transient (characterised by fast cycling between restricted and derestricted states) and continuous (characterised by rare changes between the two states). The risk of a herd being placed under restriction was dominated by predictors related to cattle movements. The probability of derestriction increased with more regular testing. Some risks affected both transitions, namely loge mean size of neighbouring herds in the test-year, whether the herd bred its own replacements and the foot and mouth disease indicator of whether a bTB test was done between February 2002 and January 2003, possibly because the underlying true state of the herd, as infected or not, meant that these factors increased or reduced the risk of HBD. These results highlight that management of bTB is dependent on the true underlying herd status of bTB infection and that some confusion of the benefits or otherwise of some management practices, e.g. using home bred replacements can be explained by this underlying status. [Copyright &y& Elsevier]

The effect of genetic variation on the neutralizing antibody response to respiratory syncytial virus (RSV) is poorly understood. In this study, acute- and convalescent-phase sera were evaluated against different RSV strains. The proportion of individuals with homologous seroconversion was greater than that among individuals with heterologous seroconversion among those infected with RSV group A (50% vs 12.5%; P = .0005) or RSV group B (40% vs 8%; P = .008). Seroconversion to BA genotype or non-BA genotype test viruses was similar among individuals infected with non-BA virus (35% vs 50%; P = .4) or BA virus (50% vs 65%; P = .4). The RSV neutralizing response is group specific. The BA-associated genetic change did not confer an ability to escape neutralizing responses to previous non-BA viruses. [ABSTRACT FROM PUBLISHER]

Background: Imperfect diagnostic testing reduces the power to detect significant predictors in classical cross-sectional studies. Assuming that the misclassification in diagnosis is random this can be dealt with by increasing the sample size of a study. However, the effects of imperfect tests in longitudinal data analyses are not as straightforward to anticipate, especially if the outcome of the test influences behaviour. The aim of this paper is to investigate the impact of imperfect test sensitivity on the determination of predictor variables in a longitudinal study. Methodology/Principal Findings: To deal with imperfect test sensitivity affecting the response variable, we transformed the observed response variable into a set of possible temporal patterns of true disease status, whose prior probability was a function of the test sensitivity. We fitted a Bayesian discrete time survival model using an MCMC algorithm that treats the true response patterns as unknown parameters in the model. We applied our approach to epidemiological data of bovine tuberculosis outbreaks in England and investigated the effect of reduced test sensitivity in the determination of risk factors for the disease. We found that reduced test sensitivity led to changes to the collection of risk factors associated with the probability of an outbreak that were chosen in the 'best' model and to an increase in the uncertainty surrounding the parameter estimates for a model with a fixed set of risk factors that were associated with the response variable. Conclusions/Significance: We propose a novel algorithm to fit discrete survival models for longitudinal data where values of the response variable are uncertain. When analysing longitudinal data, uncertainty surrounding the response variable will affect the significance of the predictors and should therefore be accounted for either at the design stage by increasing the sample size or at the post analysis stage by conducting appropriate sensitivity analyses. [ABSTRACT FROM AUTHOR]

Abstract: Dichelobacter nodosus, a Gram-negative anaerobic bacterium, is the essential causative agent of footrot in sheep. Currently, depending on the clinical presentation in the field, footrot is described as benign or virulent; D. nodosus strains have also been classified as benign or virulent, but this designation is not always consistent with clinical disease. The aim of this study was to determine the diversity of the pgr gene, which encodes a putative proline-glycine repeat protein (Pgr). The pgr gene was present in all 100 isolates of D. nodosus that were examined and, based on sequence analysis had two variants, pgrA and pgrB. In pgrA, there were two coding tandem repeat regions, R1 and R2: different strains had variable numbers of repeats within these regions. The R1 and R2 were absent from pgrB. Both variants were present in strains from Australia, Sweden and the UK, however, only pgrB was detected in isolates from Western Australia. The pgrA gene was detected in D. nodosus from tissue samples from two flocks in the UK with virulent footrot and only pgrB from a flock with no virulent or benign footrot for >10 years. Bioinformatic analysis of the putative PgrA protein indicated that it contained a collagen-like cell surface anchor motif. These results suggest that the pgr gene may be a useful molecular marker for epidemiological studies. [ABSTRACT FROM AUTHOR]

Abstract: One of the cardinal features of the immune response is immune memory: the size of the secondary antibody response to vaccination reflects the amount of immune memory that has been generated in an individual by the priming dose. We construct a mathematical model of the generation of immune memory and antibody in response to hepatitis B vaccines. The model predictions are compared to post-vaccination antibody titres from eight adult vaccine trials. The model demonstrates significant differences between different vaccines in both the time taken to generate immune memory and the amount of memory generated. The model provides theoretical support for the hypothesis that a single vaccine dose can generate protective immune memory. [Copyright &y& Elsevier]

Background: The COVID-19 epidemic has differentially impacted communities across England, with regional variation in rates of confirmed cases, hospitalisations and deaths. Measurement of this burden changed substantially over the first months, as surveillance was expanded to accommodate the escalating epidemic. Laboratory confirmation was initially restricted to clinical need ("pillar 1") before expanding to community-wide symptomatics ("pillar 2"). This study aimed to ascertain whether inconsistent measurement of case data resulting from varying testing coverage could be reconciled by drawing inference from COVID-19-related deaths.Methods: We fit a Bayesian spatio-temporal model to weekly COVID-19-related deaths per local authority (LTLA) throughout the first wave (1 January 2020-30 June 2020), adjusting for the local epidemic timing and the age, deprivation and ethnic composition of its population. We combined predictions from this model with case data under community-wide, symptomatic testing and infection prevalence estimates from the ONS infection survey, to infer the likely trajectory of infections implied by the deaths in each LTLA.Results: A model including temporally- and spatially-correlated random effects was found to best accommodate the observed variation in COVID-19-related deaths, after accounting for local population characteristics. Predicted case counts under community-wide symptomatic testing suggest a total of 275,000-420,000 cases over the first wave - a median of over 100,000 additional to the total confirmed in practice under varying testing coverage. This translates to a peak incidence of around 200,000 total infections per week across England. The extent to which estimated total infections are reflected in confirmed case counts was found to vary substantially across LTLAs, ranging from 7% in Leicester to 96% in Gloucester with a median of 23%.Conclusions: Limitations in testing capacity biased the observed trajectory of COVID-19 infections throughout the first wave. Basing inference on COVID-19-related mortality and higher-coverage testing later in the time period, we could explore the extent of this bias more explicitly. Evidence points towards substantial under-representation of initial growth and peak magnitude of infections nationally, to which different parts of the country contribute unequally. [ABSTRACT FROM AUTHOR]

The SIR (susceptible–infectious–resistant) and SIS (susceptible–infectious–susceptible) frameworks for infectious disease have been extensively studied and successfully applied. They implicitly assume the upper and lower limits of the range of possibilities for host immune response. However, the majority of infections do not fall into either of these extreme categories. We combine two general avenues that straddle this range: temporary immune protection (immunity wanes over time since infection), and partial immune protection (immunity is not fully protective but reduces the risk of reinfection). We present a systematic analysis of the dynamics and equilibrium properties of these models in comparison to SIR and SIS, and analyse the outcome of vaccination programmes. We describe how the waning of immunity shortens inter-epidemic periods, and poses major difficulties to disease eradication. We identify a “reinfection threshold” in transmission when partial immunity is included. Below the reinfection threshold primary infection dominates, levels of infection are low, and vaccination is highly effective (approximately an SIR model). Above the reinfection threshold reinfection dominates, levels of infection are high, and vaccination fails to protect (approximately an SIS situation). This association between high prevalence of infection and vaccine failure emphasizes the problems of controlling recurrent infections in high-burden regions. However, vaccines that induce a better protection than natural infection have the potential to increase the reinfection threshold, and therefore constitute interventions with a surprisingly high capacity to reduce infection where reduction is most needed. [Copyright &y& Elsevier]

Many countries have banned groups and gatherings as part of their response to the pandemic caused by the coronavirus, SARS-CoV-2. Although there are outbreak reports involving mass gatherings, the contribution to overall transmission is unknown. We used data from a survey of social contact behaviour that specifically asked about contact with groups to estimate the population attributable fraction (PAF) due to groups as the relative change in the basic reproduction number when groups are prevented. Groups of 50+ individuals accounted for 0.5% of reported contact events, and we estimate that the PAF due to groups of 50+ people is 5.4% (95% confidence interval 1.4%, 11.5%). The PAF due to groups of 20+ people is 18.9% (12.7%, 25.7%) and the PAF due to groups of 10+ is 25.2% (19.4%, 31.4%). Under normal circumstances with pre-COVID-19 contact patterns, large groups of individuals have a relatively small epidemiological impact; small- and medium-sized groups between 10 and 50 people have a larger impact on an epidemic. [ABSTRACT FROM AUTHOR]

This study demonstrates that an adoption of a segmenting and shielding strategy could increase the scope to partially exit COVID-19 lockdown while limiting the risk of an overwhelming second wave of infection. We illustrate this using a mathematical model that segments the vulnerable population and their closest contacts, the 'shielders'. Effects of extending the duration of lockdown and faster or slower transition to post-lockdown conditions and, most importantly, the trade-off between increased protection of the vulnerable segment and fewer restrictions on the general population are explored. Our study shows that the most important determinants of outcome are: (i) postlockdown transmission rates within the general and between the general and vulnerable segments; (ii) fractions of the population in the vulnerable and shielder segments; (iii) adherence to protective measures; and (iv) buildup of population immunity. Additionally, we found that effective measures in the shielder segment, e.g. intensive routine screening, allow further relaxations in the general population. We find that the outcome of any future policy is strongly influenced by the contact matrix between segments and the relationships between physical distancing measures and transmission rates. This strategy has potential applications for any infectious disease for which there are defined proportions of the population who cannot be treated or who are at risk of severe outcomes. [ABSTRACT FROM AUTHOR]

The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. Several cases of reinfection with SARS-CoV-2 have been documented 48-142 days after the initial infection and immunity to seasonal circulating coronaviruses is estimated to be shorter than 1 year. Using an age-structured, deterministic model, we explore potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalized individuals, a year for hospitalized individuals, and the effective reproduction number after lockdown ends is 1.2 (our worst-case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 387 000 infectious individuals and 125 000 daily new cases; threefold greater than in a scenario with permanent immunity. Our models suggest that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown in June until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary wave. Overall, our analysis presents considerations for policy makers on the longer-term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection as immunity to reinfection is not permanent. [ABSTRACT FROM AUTHOR]

Contact tracing is an important tool for allowing countries to ease lockdown policies introduced to combat SARS-CoV-2. For contact tracing to be effective, those with symptoms must self-report themselves while their contacts must self-isolate when asked. However, policies such as legal enforcement of self-isolation can create trade-offs by dissuading individuals from selfreporting. We use an existing branching process model to examine which aspects of contact tracing adherence should be prioritized. We consider an inverse relationship between self-isolation adherence and self-reporting engagement, assuming that increasingly strict self-isolation policies will result in fewer individuals self-reporting to the programme. We find that policies which increase the average duration of self-isolation, or that increase the probability that people self-isolate at all, at the expense of reduced selfreporting rate, will not decrease the risk of a large outbreak and may increase the risk, depending on the strength of the trade-off. These results suggest that policies to increase self-isolation adherence should be implemented carefully. Policies that increase self-isolation adherence at the cost of self-reporting rates should be avoided. [ABSTRACT FROM AUTHOR]

We explore strategies of contact tracing, case isolation and quarantine of exposed contacts to control the SARS-CoV-2 epidemic using a branching process model with household structure. This structure reflects higher transmission risks among household members than among non-household members. We explore strategic implementation choices that make use of household structure, and investigate strategies including two-step tracing, backwards tracing, smartphone tracing and tracing upon symptom report rather than test results. The primary model outcome is the effect of contact tracing, in combination with different levels of physical distancing, on the growth rate of the epidemic. Furthermore, we investigate epidemic extinction times to indicate the time period over which interventions must be sustained. We consider effects of non-uptake of isolation/quarantine, nonadherence, and declining recall of contacts over time. Our results find that, compared to self-isolation of cases without contact tracing, a contact tracing strategy designed to take advantage of household structure allows for some relaxation of physical distancing measures but cannot completely control the epidemic absent of other measures. Even assuming no imported cases and sustainment of moderate physical distancing, testing and tracing efforts, the time to bring the epidemic to extinction could be in the order of months to years. [ABSTRACT FROM AUTHOR]

As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (automatic selection of models and outlier detection for epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterize the main trend in an incidence. We then derive prediction intervals and classify data points outside this interval as outliers, which provides an objective criterion for identifying departures from previous trends. We also provide a method for selecting the optimal breakpoints, used to define how many recent data points are to be excluded from the trend fitting procedure. The analysis of simulated COVID-19 outbreaks suggests ASMODEE compares favourably with a state-of-art outbreak-detection algorithm while being simpler and more flexible. As such, our method could be of wider use for infectious disease surveillance. We illustrate ASMODEE using publicly available data of National Health Service (NHS) Pathways reporting potential COVID-19 cases in England at a fine spatial scale, showing that the method would have enabled the early detection of the flare-ups in Leicester and Blackburn with Darwen, two to three weeks before their respective lockdown. ASMODEE is implemented in the free R package trendbreaker. [ABSTRACT FROM AUTHOR]

Transmission of the carcinogenic liver fluke Opisthorchis viverrini is ongoing across Southeast Asia. Endemic countries within the region are in different stages of achieving control. However, evidence on which interventions are the most effective for reducing parasite transmission, and the resulting liver cancer, is currently lacking. Quantitative modelling can be used to evaluate different control measures against O. viverrini and assist the design of clinical trials. In this article we evaluate the epidemiological parameters that underpin models of O. viverrini and the data necessary for their estimation, with the aim of developing evidence-based strategies for parasite control at a national or regional level. Halting the transmission of O. viverrini is crucial to preventing cases of cholangiocarcinoma, yet there is no consensus on the best strategies for large-scale parasite control. Quantitative modelling can provide insights and guide control programmes more rapidly and using fewer resources than clinical trials. To give reliable output, models depend on making accurate assumptions and using parameters inferred from relevant datasets. Mathematical models of O. viverrini dynamics have recently been published and provide a valuable starting point. However, many key epidemiological processes remain poorly understood, including the links between parasite exposure, anthelmintic treatment, and carcinogenesis. We highlight areas where new studies are required to fill knowledge gaps. Recent developments in statistical modelling and parasite genomics provide opportunities to make rapid gains. [ABSTRACT FROM AUTHOR]

Abstract: Thresholds in transmission are responsible for critical changes in infectious disease epidemiology. The epidemic threshold indicates whether infection invades a totally susceptible population. The reinfection threshold indicates whether self-sustained transmission occurs in a population that has developed a degree of partial immunity to the pathogen (by previous infection or vaccination). In models that combine susceptible and partially immune individuals, the reinfection threshold is technically not a bifurcation of equilibria as correctly pointed out by Breban and Blower. However, we show that a branch of equilibria to a reinfection submodel bifurcates from the disease-free equilibrium as transmission crosses this threshold. Consequently, the full model indicates that levels of infection increase by two orders of magnitude and the effect of mass vaccination becomes negligible as transmission increases across the reinfection threshold. [Copyright &y& Elsevier]

Respiratory syncytial virus (RSV) is responsible for a significant burden of severe acute lower respiratory tract illness in children under 5 years old; particularly infants. Prior to rolling out any vaccination program, identification of the source of infant infections could further guide vaccination strategies. We extended a dynamic model calibrated at the individual host level initially fit to social-temporal data on shedding patterns to include whole genome sequencing data available at a lower sampling intensity. The study population was 493 individuals (55 aged < 1 year) distributed across 47 households, observed through one RSV season in coastal Kenya. We found that 58/97 (60%) of RSV-A and 65/125 (52%) of RSV-B cases arose from infection probably occurring within the household. Nineteen (45%) infant infections appeared to be the result of infection by other household members, of which 13 (68%) were a result of transmission from a household co-occupant aged between 2 and 13 years. The applicability of genomic data in studies of transmission dynamics is highly context specific; influenced by the question, data collection protocols and pathogen under investigation. The results further highlight the importance of pre-school and school-aged children in RSV transmission, particularly the role they play in directly infecting the household infant. These age groups are a potential RSV vaccination target group. [ABSTRACT FROM AUTHOR]

Background: Pre-exposure prophylaxis (PrEP) is highly effective in preventing HIV and has the potential to significantly impact the HIV epidemic. Given limited resources for HIV prevention, identifying PrEP provision strategies that maximize impact is critical. Methods: We used a stochastic individual-based network model to evaluate the direct (infections prevented among PrEP users) and indirect (infections prevented among non-PrEP users as a result of PrEP) benefits of PrEP, the person-years of PrEP required to prevent one HIV infection, and the community-level impact of providing PrEP to populations defined by gender and age in western Kenya and South Africa. We examined sensitivity of results to scale-up of antiretroviral therapy (ART) and voluntary medical male circumcision (VMMC) by comparing two scenarios: maintaining current coverage ("status quo") and rapid scale-up to meet programmatic targets ("fast-track"). Results: The community-level impact of PrEP was greatest among women aged 15–24 due to high incidence, while PrEP use among men aged 15–24 yielded the highest proportion of indirect infections prevented in the community. These indirect infections prevented continue to increase over time (western Kenya: 0.4–5.5 (status quo); 0.4–4.9 (fast-track); South Africa: 0.5–1.8 (status quo); 0.5–3.0 (fast-track)) relative to direct infections prevented among PrEP users. The number of person-years of PrEP needed to prevent one HIV infection was lower (59 western Kenya and 69 in South Africa in the status quo scenario; 201 western Kenya and 87 in South Africa in the fast-track scenario) when PrEP was provided only to women compared with only to men over time horizons of up to 5 years, as the indirect benefits of providing PrEP to men accrue in later years. Conclusions: Providing PrEP to women aged 15–24 prevents the greatest number of HIV infections per person-year of PrEP, but PrEP provision for young men also provides indirect benefits to women and to the community overall. This finding supports existing policies that prioritize PrEP use for young women, while also illuminating the community-level benefits of PrEP availability for men when resources permit. [ABSTRACT FROM AUTHOR]

Objectives: New HIV infections remain higher in women than men in sub-Saharan Africa. Preexposure prophylaxis (PrEP) is an effective HIV prevention measure, currently prioritized for those at highest risk, such as female sex workers (FSWs), for whom it is most cost-effective. However, the greatest number of HIV infections in sub-Saharan Africa occurs in women in the general population. As countries consider wider PrEP scale-up, there is a need to weigh the population-level impact, cost, and relative cost-effectiveness to inform priority setting.Methods: We developed mathematical models of HIV risk to women and derived tools to highlight key considerations for PrEP programming. The models were fitted to South Africa, Zimbabwe, and Kenya, spanning a range of HIV burden in sub-Saharan Africa. The impact, cost, and cost-effectiveness of PrEP scale-up for adolescent girls and young women (AGYW), women 25 to 34 years old, and women 35 to 49 years old were assessed, accounting for differences in population sizes and the low program retention levels reported in demonstration projects.Results: Preexposure prophylaxis could avert substantially more infections a year among women in general population than among FSW. The greatest number of infections could be averted annually among AGYW in South Africa (24-fold that for FSW). In Zimbabwe, the greatest number of infections could be averted among women 25 to 34 years old (8-fold that for FSW); and in Kenya, similarly between AGYW and women 25 to 34 years old (3-fold that for FSW). However, the unit costs of PrEP delivery for AGYW, women 25 to 34 years old, and women 35 to 49 years old would have to reduce considerably (by 70.8%-91.0% across scenarios) for scale-up to these populations to be as cost-effective as for FSW.Conclusions: Preexposure prophylaxis has the potential to substantially reduce new HIV infections in HIV-endemic countries in sub-Saharan Africa. This will necessitate PrEP being made widely available beyond those at highest individual risk and continued integration into a range of national services and at community level to significantly bring down the costs and improve cost-effectiveness. [ABSTRACT FROM AUTHOR]

Understanding of spatiotemporal transmission of infectious diseases has improved significantly in recent years. Advances in Bayesian inference methods for individual-level geo-located epidemiological data have enabled reconstruction of transmission trees and quantification of disease spread in space and time, while accounting for uncertainty in missing data. However, these methods have rarely been applied to endemic diseases or ones in which asymptomatic infection plays a role, for which additional estimation methods are required. Here, we develop such methods to analyze longitudinal incidence data on visceral leishmaniasis (VL) and its sequela, post-kala-azar dermal leishmaniasis (PKDL), in a highly endemic community in Bangladesh. Incorporating recent data on VL and PKDL infectiousness, we show that while VL cases drive transmission when incidence is high, the contribution of PKDL increases significantly as VL incidence declines (reaching 55% in this setting). Transmission is highly focal: 85% of mean distances from inferred infectors to their secondary VL cases were <300 m, and estimated average times from infector onset to secondary case infection were <4 mo for 88% of VL infectors, but up to 2.9 y for PKDL infectors. Estimated numbers of secondary cases per VL and PKDL case varied from 0 to 6 and were strongly correlated with the infector's duration of symptoms. Counterfactual simulations suggest that prevention of PKDL could have reduced overall VL incidence by up to 25%. These results highlight the need for prompt detection and treatment of PKDL to achieve VL elimination in the Indian subcontinent and provide quantitative estimates to guide spatiotemporally targeted interventions against VL. [ABSTRACT FROM AUTHOR]

Background: The elimination programme for visceral leishmaniasis (VL) in India has seen great progress, with total cases decreasing by over 80% since 2010 and many blocks now reporting zero cases from year to year. Prompt diagnosis and treatment is critical to continue progress and avoid epidemics in the increasingly susceptible population. Short-term forecasts could be used to highlight anomalies in incidence and support health service logistics. The model which best fits the data is not necessarily most useful for prediction, yet little empirical work has been done to investigate the balance between fit and predictive performance. Methodology/Principal findings: We developed statistical models of monthly VL case counts at block level. By evaluating a set of randomly-generated models, we found that fit and one-month-ahead prediction were strongly correlated and that rolling updates to model parameters as data accrued were not crucial for accurate prediction. The final model incorporated auto-regression over four months, spatial correlation between neighbouring blocks, and seasonality. Ninety-four percent of 10-90% prediction intervals from this model captured the observed count during a 24-month test period. Comparison of one-, three- and four-month-ahead predictions from the final model fit demonstrated that a longer time horizon yielded only a small sacrifice in predictive power for the vast majority of blocks. Conclusions/Significance: The model developed is informed by routinely-collected surveillance data as it accumulates, and predictions are sufficiently accurate and precise to be useful. Such forecasts could, for example, be used to guide stock requirements for rapid diagnostic tests and drugs. More comprehensive data on factors thought to influence geographic variation in VL burden could be incorporated, and might better explain the heterogeneity between blocks and improve uniformity of predictive performance. Integration of the approach in the management of the VL programme would be an important step to ensuring continued successful control. Author summary: This paper demonstrates a statistical modelling approach for forecasting of monthly visceral leishmaniasis (VL) incidence at block level in India, which could be used to tailor control efforts according to local estimates and monitor deviations from the currently decreasing trend. By fitting a variety of models to four years of historical data and assessing predictions within a further 24-month test period, we found that the model which best fit the observed data also showed the best predictive performance, and predictive accuracy was maintained when making rolling predictions up to four months ahead of the observed data. Since there is a two-month delay between reporting and processing of the data, predictive power more than three months ahead of current data is crucial to make forecasts which can feasibly be acted upon. Some heterogeneity remains in predictive power across the study region which could potentially be improved using unit-specific data on factors believed to be associated with reported VL incidence (e.g. age distribution, socio-economic status and climate). [ABSTRACT FROM AUTHOR]

Background: Control of visceral leishmaniasis (VL) on the Indian subcontinent relies on prompt detection and treatment of symptomatic cases. Detection efforts influence the observed VL incidence and how well it reflects the underlying true incidence. As control targets are defined in terms of observed cases, there is an urgent need to understand how changes in detection delay and population coverage of improved detection affect VL control.Methods: Using a mathematical model for transmission and control of VL, we predict the impact of reduced detection delays and/or increased population coverage of the detection programs on observed and true VL incidence and mortality.Results: Improved case detection, either by higher coverage or reduced detection delay, causes an initial rise in observed VL incidence before a reduction. Relaxation of improved detection may lead to an apparent temporary (1 year) reduction in VL incidence, but comes with a high risk of resurging infection levels. Duration of symptoms in detected cases shows an unequivocal association with detection effort.Conclusions: VL incidence on its own is not a reliable indicator of the performance of case detection programs. Duration of symptoms in detected cases can be used as an additional marker of the performance of case detection programs. [ABSTRACT FROM AUTHOR]

Background: As the World Health Organization seeks to eliminate trachoma by 2020, countries are beginning to control the transmission of trachomatous inflammation-follicular (TF) and discontinue mass drug administration (MDA) with oral azithromycin. We evaluated the effect of MDA discontinuation on TF1-9 prevalence at the district level.Methods: We extracted from the available data districts with an impact survey at the end of their program cycle that initiated discontinuation of MDA (TF1-9 prevalence <5%), followed by a surveillance survey conducted to determine whether TF1-9 prevalence remained below the 5% threshold, warranting discontinuation of MDA. Two independent analyses were performed, 1 regression based and 1 simulation based, that assessed the change in TF1-9 from the impact survey to the surveillance survey.Results: Of the 220 districts included, TF1-9 prevalence increased to >5% from impact to surveillance survey in 9% of districts. Regression analysis indicated that impact survey TF1-9 prevalence was a significant predictor of surveillance survey TF1-9 prevalence. The proportion of simulations with >5% TF1-9 prevalence in the surveillance survey was 2%, assuming the survey was conducted 4 years after MDA.Conclusion: An increase in TF1-9 prevalence may represent disease resurgence but could also be due to measurement error. Improved diagnostic tests are crucial to elimination of TF1-9 as a public health problem. [ABSTRACT FROM AUTHOR]

The World Health Organization (WHO) has set elimination as a public health problem (EPHP) as a goal for schistosomiasis. As the WHO treatment guidelines for schistosomiasis are currently under revision, we investigate whether school-based or community-wide treatment strategies are required for achieving the EPHP goal. In low- to moderate-transmission settings with good school enrolment, we find that school-based treatment is sufficient for achieving EPHP. However, community-wide treatment is projected to be necessary in certain high-transmission settings as well as settings with low school enrolment. Hence, the optimal treatment strategy depends on setting-specific factors such as the species present, prevalence prior to treatment, and the age profile of infection. [ABSTRACT FROM AUTHOR]

As neglected tropical disease programs look to consolidate the successes of moving towards elimination, we need to understand the dynamics of transmission at low prevalence to inform surveillance strategies for detecting elimination and resurgence. In this special collection, modelling insights are used to highlight drivers of local elimination, evaluate strategies for detecting resurgence, and show the importance of rational spatial sampling schemes for several neglected tropical diseases (specifically schistosomiasis, soil-transmitted helminths, lymphatic filariasis, trachoma, onchocerciasis, visceral leishmaniasis, and gambiense sleeping sickness). [ABSTRACT FROM AUTHOR]

Background: Melioidosis is an infectious disease that is transmitted mainly through contact with contaminated soil or water, and exhibits marked seasonality in most settings, including Southeast Asia. In this study, we used mathematical modelling to examine the impacts of such demographic changes on melioidosis incidence, and to predict the disease burden in a developing country such as Thailand. Methodology/Principal findings: A melioidosis infection model was constructed which included demographic data, diabetes mellitus (DM) prevalence, and melioidosis disease processes. The model was fitted to reported melioidosis incidence in Thailand by age, sex, and geographical area, between 2008 and 2015, using a Bayesian Markov Chain Monte Carlo (MCMC) approach. The model was then used to predict the disease burden and future trends of melioidosis incidence in Thailand. Our model predicted two-fold higher incidence rates of melioidosis compared with national surveillance data from 2015. The estimated incidence rates among males were two-fold greater than those in females. Furthermore, the melioidosis incidence rates in the Northeast region population, and among the transient population, were more than double compared to the non-Northeast region population. The highest incidence rates occurred in males aged 45–59 years old for all regions. The average incidence rate of melioidosis between 2005 and 2035 was predicted to be 11.42 to 12.78 per 100,000 population per year, with a slightly increasing trend. Overall, it was estimated that about half of all cases of melioidosis were symptomatic. In addition, the model suggested a greater susceptibility to melioidosis in diabetic compared with non-diabetic individuals. Conclusions/Significance: The increasing trend of melioidosis incidence rates was significantly higher among working-age Northeast and transient populations, males aged ≥45 years old, and diabetic individuals. Targeted intervention strategies, such as health education and awareness raising initiatives, should be implemented on high-risk groups, such as those living in the Northeast region, and the seasonally transient population. [ABSTRACT FROM AUTHOR]

We report on infection patterns in 5 households (78 participants) delineating the natural history of human rhinovirus (HRV). Nasopharyngeal collections were obtained every 3–4 days irrespective of symptoms, over a 6-month period, with molecular screening for HRV and typing by sequencing VP4/VP2 junction. Overall, 311/3468 (8.9%) collections were HRV positive: 256 were classified into 3 species: 104 (40.6%) HRV-A; 14 (5.5%) HRV-B, and 138 (53.9%) HRV-C. Twenty-six known HRV types (13 HRV-A, 3 HRV-B, and 10 HRV-C) were identified (A75, C1, and C35 being most frequent). We observed continuous invasion and temporal clustering of HRV types in households (range 5–13 over 6 months). Intrahousehold transmission was independent of clinical status but influenced by age. Most (89.0%) of HRV infection episodes were limited to <14 days. Individual repeat infections were frequent (range 1–7 over 6 months), decreasing with age, and almost invariably heterotypic, indicative of lasting type-specific immunity and low cross-type protection. [ABSTRACT FROM AUTHOR]