Convergence of SARS-CoV-2 spike antibody levels to a population immune setpoint.

BACKGROUND: Individual immune responses to SARS-CoV-2 are well-studied, while the combined effect of these responses on population-level immune dynamics remains poorly understood. Given the key role of population immunity on pathogen transmission, delineation of the factors that drive population immune evolution has critical public health implications. METHODS: We enrolled individuals 5 years and older selected using a multistage cluster survey approach in the Northwest and Southeast of the Dominican Republic. Paired blood samples were collected mid-pandemic (Aug 2021) and late pandemic (Nov 2022). We measured serum pan-immunoglobulin antibodies against the SARS-CoV-2 spike protein. Generalized Additive Models (GAMs) and random forest models were used to analyze the relationship between changes in antibody levels and various predictor variables. Principal component analysis and partial dependence plots further explored the relationships between predictors and antibody changes. FINDINGS: We found a transformation in the distribution of antibody levels from an irregular to a normalized single peak Gaussian distribution that was driven by titre-dependent boosting. This led to the convergence of antibody levels around a common immune setpoint, irrespective of baseline titres and vaccination profile. INTERPRETATION: Our results suggest that titre-dependent kinetics driven by widespread transmission direct the evolution of population immunity in a consistent manner. These findings have implications for targeted vaccination strategies and improved modeling of future transmission, providing a preliminary blueprint for understanding population immune dynamics that could guide public health and vaccine policy for SARS-CoV-2 and potentially other pathogens. FUNDING: The study was primarily funded by the Centers for Disease Control and Prevention grant U01GH002238 (EN). Salary support was provided by Wellcome Trust grant 206250/Z/17/Z (AK) and the Australian National Health and Medical Research Council Investigator grant APP1158469 (CLL).

Using health literacy principles to improve understanding of evolving evidence in health emergencies: Optimisation and evaluation of a COVID-19 vaccination risk-benefit calculator.

BACKGROUND: Risk communication tools based on epidemiological models can help inform decision-making, but must be responsive to health literacy needs to be effective. To facilitate informed choice about risks and benefits of COVID-19 vaccination, an epidemiological model called the COVID-19 Risk Calculator (CoRiCal) tool was developed by a multi-disciplinary team. AIM: This paper demonstrates how to use health literacy principles to improve consumer understanding of COVID-19 and vaccine effects, using a range of methods that could be applied to any health emergency. METHODS: Stage 1: Health literacy optimisation and user testing to reduce improve understandability (n = 19). Stage 2: Experiments to explore the effect of risk communication formats on perceived understanding including probability, graphs, evaluative labels and comparison risks (n = 207). Stage 3: Randomised controlled trial (n = 2005) with 4 arms: 1) standard government information; 2) standard CoRiCal output based on bar graphs; 3) animation explaining bar graphs in "x per million" format; 4) animation explaining bar graphs in "1 in x chance" format. The primary outcome was knowledge about COVID-19 risk. RESULTS: Stage 1 reduced the complexity of the text and graphs. Stage 2 showed that different risk communication formats change perceived understanding, with a preference for evaluative labels across 2 experiments and some indication people with lower health literacy had a greater preference for bar graphs. Stage 3 showed both animations increased knowledge compared to standard government information. There was no difference between the probability formats, or by health literacy level. DISCUSSION: The results showed that simple explanations of complex epidemiological models improve knowledge about COVID-19 and vaccination. This demonstrates how health literacy design principles and short animations can be used to support informed decision making about health emergencies.

Molecular xenomonitoring as an indicator of microfilaraemia prevalence for lymphatic filariasis in Samoa in 2019.

BACKGROUND: Lymphatic filariasis (LF) is a globally significant, vector-borne, neglected tropical disease that can result in severe morbidity and disability. As the World Health Organization (WHO) Global Programme to Eliminate Lymphatic Filariasis makes progress towards LF elimination, there is greater need to develop sensitive strategies for post-intervention surveillance. Molecular xenomonitoring (MX), the detection of pathogen DNA in vectors, may provide a sensitive complement to traditional human-based surveillance techniques, including detection of circulating filarial antigen and microfilaraemia (Mf). This study aims to explore the relationship between human Mf prevalence and the prevalence of polymerase chain reaction (PCR)-positive mosquitoes using MX. METHODS: This study compared Mf and MX results from a 2019 community-based survey conducted in 35 primary sampling units (PSUs) in Samoa. This study also investigated concordance between presence and absence of PCR-positive mosquitoes and Mf-positive participants at the PSU level, and calculated sensitivity and negative predictive values for each indicator using presence of any Mf-positive infection in humans or PCR-positive mosquitoes as a reference. Correlation between prevalence of filarial DNA in mosquitoes and Mf in humans was estimated at the PSU and household/trap level using mixed-effect Bayesian multilevel regression analysis. RESULTS: Mf-positive individuals were identified in less than half of PSUs in which PCR-positive mosquito pools were present (13 of 28 PSUs). Prevalence of PCR-positive mosquitoes (each species separately) was positively correlated with Mf prevalence in humans at the PSU level. Analysed at the species level, only Aedes polynesiensis demonstrated strong evidence of positive correlation (r) with human Mf prevalence at both PSU (r: 0.5, 95% CrI 0.1-0.8) and trap/household levels (r: 0.6, 95% CrI 0.2-0.9). CONCLUSIONS: Findings from this study demonstrate that MX can be a sensitive surveillance method for identifying residual infection in low Mf prevalence settings. MX identified more locations with signals of transmission than Mf-testing. Strong correlation between estimated PCR-positive mosquitoes in the primary vector species and Mf in humans at small spatial scales demonstrates the utility of MX as an indicator for LF prevalence in Samoa and similar settings. Further investigation is needed to develop MX guidelines to strengthen the ability of MX to inform operational decisions.

Field laboratory comparison of STANDARD Q Filariasis Antigen Test (QFAT) with Bioline Filariasis Test Strip (FTS) for the detection of Lymphatic Filariasis in Samoa, 2023.

BACKGROUND: To monitor the progress of lymphatic filariasis (LF) elimination programmes, field surveys to assess filarial antigen (Ag) prevalence require access to reliable, user-friendly rapid diagnostic tests. We aimed to evaluate the performance of the new Q Filariasis Antigen Test (QFAT) with the currently recommended Filariasis Test Strip (FTS) for detecting the Ag of Wuchereria bancrofti, the causative agent of LF, under field laboratory conditions. METHODOLOGY/PRINCIPAL FINDINGS: During an LF survey in Samoa, 344 finger-prick blood samples were tested using FTS and QFAT. Microfilariae (Mf) status was determined from blood slides prepared from any sample that reported Ag-positive by either Ag-test. Each test was re-read at 1 hour and the next day to determine the stability of results over time. Overall Ag-positivity by FTS was 29.0% and 30.2% by QFAT. Concordance between the two tests was 93.6% (kappa = 0.85). Of the 101 Mf slides available, 39.6% were Mf-positive, and all were Ag-positive by both tests. Darker test line intensities from Ag-positive FTS were found to predict Mf-positivity (compared to same/lighter line intensities). QFAT had significantly higher reported test result changes than FTS, mostly reported the next day, but fewer changes were reported between 10 minutes to 1hour. The field laboratory team preferred QFAT over FTS due to the smaller blood volume required, better usability, and easier readability. CONCLUSION/SIGNIFICANCE: QFAT could be a suitable and user-friendly diagnostic alternative for use in the monitoring and surveillance of LF in field surveys based on its similar performance to FTS under field laboratory conditions.

Measuring what matters: Context-specific indicators for assessing immunisation performance in Pacific Island Countries and Areas.

Increasing countries' access to data can improve immunisation coverage through evidence-based decision-making. However, data collection and reporting is resource-intensive, so needs to be pragmatic, especially in low-and-middle-income countries. We aimed to identify which indicators are most important for measuring, and improving, national immunisation performance in Pacific Island Countries (PICs). We conducted an expert elicitation study, asking 13 experts involved in delivering immunisation programs, decision-makers, health information specialists, and global development partners across PICs to rate 41 indicators based on their knowledge of the feasibility and relevance of each indicator. We also asked experts their preferences for indicators to be retained or removed from a list of indicators for PICs. Experts participated in two rating rounds, with a discussion on the reasons for ratings before the second round. We calculated mean scores for feasibility and relevance, and ranked indicators based on experts' preferences and mean scores. We used framework analysis to identify reasons for selecting indicators. Experts agreed that certain indicators were essential to measure (e.g. data use in program planning and measles vaccination coverage), but preferences varied for most indicators. Preferences to include indicators in a set of indicators for PICs moderately correlated with scores for relevance (r = 0.68) and feasibility (r = 0.56). In discussions, experts highlighted usefulness for decision-making and ease of data collection, reporting and interpretation as the main reasons driving indicator selection. Country-specific factors such as health system factors, roles and influence of various immunisation actors, and macro-level factors (namely population size, distribution and mobility) affected relevance and feasibility, leading us to conclude that a single set of indicators for all PICs is inappropriate. Rather than having a strict set of indicators that all countries must measure and report against, performance indicators should be flexible, country-specific, and selected in consultation with immunisation actors who collect and use the data.

Anti-filarial antibodies are sensitive indicators of lymphatic filariasis transmission and enable identification of high-risk populations and hotspots.

OBJECTIVES: Circulating filarial antigen (Ag) is used by elimination programs to monitor lymphatic filariasis (LF) transmission; however, antifilarial antibodies (Ab) may be more sensitive than Ag for detecting LF. Our objectives were to describe Ab seroprevalence, identify risk factors for Ab seropositivity, investigate age-specific associations between Ag and Ab, and evaluate geographic clustering of seropositivity. METHODS: Community-based serosurveys of participants aged ≥5 years were conducted in 35 primary sampling units (PSUs). Ag-positivity was detected using Alere™ Filariasis Test Strips and Ab-seropositivity using multiplex bead assays. Seroprevalence was adjusted for study design. RESULTS: Of 3795 participants (range:5-90 years), adjusted prevalence for Ag, Bm14 Ab, Wb123 Ab, and Bm33 Ab were 3.7% (n=117), 20.3% (n=583), 32.2% (n=987), and 51.0% (n=1659), respectively. Male sex, older age, and residents of suspected hotspots had higher odds of seropositivity to all seromarkers. Seroprevalence was lower in 5-9-year-olds vs ≥10-year-olds (P<0.001). Clustering was significantly higher in households (intra-cluster correlation for Ag:0.45; Bm14 Ab:0.32; Bm33 Ab:0.31; Wb123 Ab:0.29) compared to PSUs or region. CONCLUSIONS: Abs enabled identification of risk factors for seropositivity and geographical clustering to inform targeted interventions for LF programmes. Further research is needed to define Ab thresholds for active versus past infection and elimination targets.

Ongoing transmission of lymphatic filariasis in Samoa 4.5 years after one round of triple-drug mass drug administration.

BACKGROUND: Lymphatic filariasis (LF) remains a significant global issue. To eliminate LF as a public health problem, the World Health Organization (WHO) recommends multiple rounds of mass drug administration (MDA). In certain scenarios, including when elimination targets have not been met with two-drug MDA, triple-drug MDA (using ivermectin, diethylcarbamazine and albendazole) is recommended. In this study, we report on antigen (Ag) and microfilaria (Mf) prevalence in eight primary sampling units (PSUs) in Samoa 4.5 years after one round of triple-drug MDA. METHODOLOGY: In 2023, community surveys were conducted in eight PSUs that had been surveyed previously in 2018 (between 1.5 and 3.5 months post triple-drug MDA) and 2019 (six to eight-months post triple-drug MDA). Fifteen houses were randomly selected in each PSU with household members aged ≥ 5 years invited to participate. Blood samples were tested for Ag and Mf. PRINCIPAL FINDINGS: Ag-positive participants were observed in six of the eight PSUs, and Ag prevalence was significantly above the 1% threshold in four PSUs. The presence of Mf-positive participants in five PSUs confirms the presence of residual active infections. CONCLUSIONS/SIGNIFICANCE: This study provides evidence of persistent LF transmission in Samoa 4.5 years after one round of triple-drug MDA, confirming that one round was insufficient for interruption of transmission in this setting. Our findings highlight the negative impact of delaying MDA rounds, for example, due to public health emergencies.

Trust and COVID-19 vaccine hesitancy in the Dominican Republic: a national cross-sectional household survey, June-October 2021.

OBJECTIVE: This study investigates the role of trust in shaping COVID-19 vaccine acceptance in the Dominican Republic (DR) during the COVID-19 pandemic. DESIGN: Cross-sectional household survey. SETTING: Randomly selected households across 134 clusters in the DR, from 30 June 2021 to 12 October 2021. PARTICIPANTS: 5999 participants ≥16 years of age were enrolled. OUTCOME MEASURES: COVID-19 vaccine hesitancy (CVH) data were collected from participants ≥16 years of age and analysed as both an ordinal and binary variable. RESULTS: Overall, CVH was low (5.2% (95% CI 4.6% to 5.8%)), but more common among younger individuals, women and individuals of Mestizo ethnicity. Higher trust in local government, national government, scientists and local doctors (considered official sources) was associated with lower odds of CVH (OR 0.89 (95% CI 0.72 to 0.88), 0.89 (95% CI 0.81 to 0.98), 0.87 (95% CI 0.80 to 0.94) and 0.70 (95% CI 0.62 to 0.80), respectively). Higher trust in religious leaders, social media and traditional media (considered unofficial sources) was associated with higher odds of CVH, with respective ORs of 1.32 (95% CI 1.18 to 1.47), 1.30 (95% CI 1.19 to 1.41) and 1.08 (95% CI 0.97 to 1.22). CONCLUSION: We report findings on CVH from a national household survey in the DR and identify overall low rates of CVH but marked heterogeneity by age, gender and ethnicity. Trust in unofficial versus official sources of information is associated with increased CVH. These findings highlight and quantify the importance of trust as a key parameter when considering public health communication strategies.

Using Regional Sero-Epidemiology SARS-CoV-2 Anti-S Antibodies in the Dominican Republic to Inform Targeted Public Health Response.

Incidence of COVID-19 has been associated with sociodemographic factors. We investigated variations in SARS-CoV-2 seroprevalence at sub-national levels in the Dominican Republic and assessed potential factors influencing variation in regional-level seroprevalence. Data were collected in a three-stage cross-sectional national serosurvey from June to October 2021. Seroprevalence of antibodies against the SARS-CoV-2 spike protein (anti-S) was estimated and adjusted for selection probability, age, and sex. Multilevel logistic regression was used to estimate the effect of covariates on seropositivity for anti-S and correlates of 80% protection (PT80) against symptomatic infection for the ancestral and Delta strains. A total of 6683 participants from 134 clusters in all 10 regions were enrolled. Anti-S, PT80 for the ancestral and Delta strains odds ratio varied across regions, Enriquillo presented significant higher odds for all outcomes compared with Yuma. Compared to being unvaccinated, receiving ≥2 doses of COVID-19 vaccine was associated with a significantly higher odds of anti-S positivity (OR 85.94, [10.95-674.33]) and PT80 for the ancestral (OR 4.78, [2.15-10.62]) and Delta strains (OR 3.08, [1.57-9.65]) nationally and also for each region. Our results can help inform regional-level public health response, such as strategies to increase vaccination coverage in areas with low population immunity against currently circulating strains.

Scabies prevalence after ivermectin-based mass drug administration for lymphatic filariasis, Samoa 2018-2019.

BACKGROUND: Scabies is a common skin infestation caused by the Sarcoptes scabei mite. Ivermectin, one of three drugs used in mass drug administration (MDA) for lymphatic filariasis, is also effective for treating scabies. Ivermectin-based MDA was first conducted in Samoa in August 2018, with ivermectin being offered to those aged ≥5 years. Here, we report scabies prevalence in Samoa after MDA. METHODS: We conducted household surveys 1.5-3.5 months (Survey 1) and 6-8 months (Survey 2) after the 2018 MDA in 35 primary sampling units. We conducted clinical examination for scabies-like rash and used International Alliance for the Control of Scabies classification criteria. We estimated scabies prevalence by age, gender and region. Multivariable logistic regression was used to assess factors associated with prevalence. RESULTS: We surveyed 2868 people (499 households) and 2796 people (544 households) aged 0-75 years in Surveys 1 and 2, respectively. Scabies prevalence increased from 2.4% (95% CI 2.1-2.7%) to 4.4% (95% CI 4.0-4.9%) between surveys. Scabies was associated with younger age (0-4 years: aOR 3.5 [2.9-4.2]; 5-15 years: aOR 1.6 [1.4-1.8] compared to ≥16 years), female gender (aOR 1.2 [95% CI 1.1-1.4]; region (aOR range from 1.4 [1.1-1.7] to 2.5 [2.1-3.1] between regions), large households (aOR 2.6 [2.0-3.4] households ≥13), and not taking MDA in 2018 (aOR 1.3 [95% CI 1.1-1.6]). CONCLUSIONS: We found moderate prevalence of scabies in two population-representative surveys conducted within 8 months of the 2018 MDA for lymphatic filariasis. Prevalence appeared to increase between the surveys, and ongoing surveillance is recommended, particularly in young children.

A decision support tool for risk-benefit analysis of Japanese encephalitis vaccine in travellers.

BACKGROUND: During pre-travel consultations, clinicians and travellers face the challenge of weighing the risks verus benefits of Japanese encephalitis (JE) vaccination due to the high cost of the vaccine, low incidence in travellers (~1 in 1 million), but potentially severe consequences (~30% case-fatality rate). Personalised JE risk assessment based on the travellers' demographics and travel itinerary is challenging using standard risk matrices. We developed an interactive digital tool to estimate risks of JE infection and severe health outcomes under different scenarios to facilitate shared decision-making between clinicians and travellers. METHODS: A Bayesian network (conditional probability) model risk-benefit analysis of JE vaccine in travellers was developed. The model considers travellers' characteristics (age, sex, co-morbidities), itinerary (destination, departure date, duration, setting of planned activities) and vaccination status to estimate the risks of JE infection, the development of symptomatic disease (meningitis, encephalitis), clinical outcomes (hospital admission, chronic neurological complications, death) and adverse events following immunization. RESULTS: In low-risk travellers (e.g. to urban areas for <1 month), the risk of developing JE and dying is low (<1 per million) irrespective of the destination; thus, the potential impact of JE vaccination in reducing the risk of clinical outcomes is limited. In high-risk travellers (e.g. to rural areas in high JE incidence destinations for >2 months), the risk of developing symptomatic disease and mortality is estimated at 9.5 and 1.4 per million, respectively. JE vaccination in this group would significantly reduce the risk of symptomatic disease and mortality (by ~80%) to 1.9 and 0.3 per million, respectively. CONCLUSION: The JE tool may assist decision-making by travellers and clinicians and could increase JE vaccine uptake. The tool will be updated as additional evidence becomes available. Future work needs to evaluate the usability of the tool. The interactive, scenario-based, personalised JE vaccine risk-benefit tool is freely available on www.VaxiCal.com.

Mapping the risk of respiratory infections using suburban district areas in a large city in Colombia.

BACKGROUND: Acute respiratory infections (ARI) in Cúcuta -Colombia, have a comparatively high burden of disease associated with high public health costs. However, little is known about the epidemiology of these diseases in the city and its distribution within suburban areas. This study addresses this gap by estimating and mapping the risk of ARI in Cúcuta and identifying the most relevant risk factors. METHODS: A spatial epidemiological analysis was designed to investigate the association of sociodemographic and environmental risk factors with the rate of ambulatory consultations of ARI in urban sections of Cúcuta, 2018. The ARI rate was calculated using a method for spatial estimation of disease rates. A Bayesian spatial model was implemented using the Integrated Nested Laplace Approximation approach and the Besag-York-Mollié specification. The risk of ARI per urban section and the hotspots of higher risk were also estimated and mapped. RESULTS: A higher risk of IRA was found in central, south, north and west areas of Cúcuta after adjusting for sociodemographic and environmental factors, and taking into consideration the spatial distribution of the city's urban sections. An increase of one unit in the percentage of population younger than 15 years; the Index of Multidimensional Poverty and the rate of ARI in the migrant population was associated with a 1.08 (1.06-1.1); 1.04 (1.01-1.08) and 1.25 (1.22-1.27) increase of the ARI rate, respectively. Twenty-four urban sections were identified as hotspots of risk in central, south, north and west areas in Cucuta. CONCLUSION: Sociodemographic factors and their spatial patterns are determinants of acute respiratory infections in Cúcuta. Bayesian spatial hierarchical models can be used to estimate and map the risk of these infections in suburban areas of large cities in Colombia. The methods of this study can be used globally to identify suburban areas and or specific communities at risk to support the implementation of prevention strategies and decision-making in the public and private health sectors.

Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics.

Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradigm. In this paper, we touch on six modern opportunities and challenges in applied Bayesian statistics: intelligent data collection, new data sources, federated analysis, inference for implicit models, model transfer and purposeful software products. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'.

SARS-CoV-2 seroprevalence, cumulative infections, and immunity to symptomatic infection - A multistage national household survey and modelling study, Dominican Republic, June-October 2021.

Background: Population-level SARS-CoV-2 immunological protection is poorly understood but can guide vaccination and non-pharmaceutical intervention priorities. Our objective was to characterise cumulative infections and immunological protection in the Dominican Republic. Methods: Household members ≥5 years were enrolled in a three-stage national household cluster serosurvey in the Dominican Republic. We measured pan-immunoglobulin antibodies against the SARS-CoV-2 spike (anti-S) and nucleocapsid glycoproteins, and pseudovirus neutralising activity against the ancestral and B.1.617.2 (Delta) strains. Seroprevalence and cumulative prior infections were weighted and adjusted for assay performance and seroreversion. Binary classification machine learning methods and pseudovirus neutralising correlates of protection were used to estimate 50% and 80% protection against symptomatic infection. Findings: Between 30 Jun and 12 Oct 2021 we enrolled 6683 individuals from 3832 households. We estimate that 85.0% (CI 82.1-88.0) of the ≥5 years population had been immunologically exposed and 77.5% (CI 71.3-83) had been previously infected. Protective immunity sufficient to provide at least 50% protection against symptomatic SARS-CoV-2 infection was estimated in 78.1% (CI 74.3-82) and 66.3% (CI 62.8-70) of the population for the ancestral and Delta strains respectively. Younger (5-14 years, OR 0.47 [CI 0.36-0.61]) and older (≥75-years, 0.40 [CI 0.28-0.56]) age, working outdoors (0.53 [0.39-0.73]), smoking (0.66 [0.52-0.84]), urban setting (1.30 [1.14-1.49]), and three vs no vaccine doses (18.41 [10.69-35.04]) were associated with 50% protection against the ancestral strain. Interpretation: Cumulative infections substantially exceeded prior estimates and overall immunological exposure was high. After controlling for confounders, markedly lower immunological protection was observed to the ancestral and Delta strains across certain subgroups, findings that can guide public health interventions and may be generalisable to other settings and viral strains. Funding: This study was funded by the US CDC.

Spatially Explicit Environmental Factors Associated with Lymphatic Filariasis Infection in American Samoa.

Under the Global Program to Eliminate Lymphatic Filariasis (LF) American Samoa conducted seven rounds of mass drug administration (MDA) between 2000 and 2006. Subsequently, the territory passed the WHO recommended school-based transmission assessment survey (TAS) in 2011/2012 (TAS-1) and 2015 (TAS-2) but failed in 2016, when both TAS-3 and a community survey found LF antigen prevalence above what it had been in previous surveys. This study aimed to identify potential environmental drivers of LF to refine future surveillance efforts to detect re-emergence and recurrence. Data on five LF infection markers: antigen, Wb123, Bm14 and Bm33 antibodies and microfilaraemia, were obtained from a population-wide serosurvey conducted in American Samoa in 2016. Spatially explicit data on environmental factors were derived from freely available sources. Separate multivariable Poisson regression models were developed for each infection marker to assess and quantify the associations between LF infection markers and environmental variables. Rangeland, tree cover and urban cover were consistently associated with a higher seroprevalence of LF-infection markers, but to varying magnitudes between landcover classes. High slope gradient, population density and crop cover had a negative association with the seroprevalence of LF infection markers. No association between rainfall and LF infection markers was detected, potentially due to the limited variation in rainfall across the island. This study demonstrated that seroprevalence of LF infection markers were more consistently associated with topographical environmental variables, such as gradient of the slope, rather than climatic variables, such as rainfall. These results provide the initial groundwork to support the detection of areas where LF transmission is more likely to occur, and inform LF elimination efforts through better understanding of the environmental drivers.

Guidelines for selecting an appropriate currency in biodiversity offset transactions.

When designing biodiversity offset transactions, selecting the appropriate currency for measuring losses and gains to biodiversity is crucial. Poorly designed currencies reduce the likelihood that the proposed offset will sufficiently compensate for the development impact on the affected biota. We present a framework for identifying appropriate offset currencies for terrestrial biodiversity features, either vegetation communities or particular species. The guidelines were developed based on a review of issues and solutions presented in the existing literature, including government policies and guidance. We assert that while benchmark-based condition scores provide a suitable offset transaction currency for vegetation communities, this approach is also commonly applied to individual species based on the often-unproven assumption that vegetation quality is a proxy for the value of a site to that species. We argue that species are better served by species-specific currencies based on either species abundance, or the suitability and amount of the habitat available. For species where it is practical and meaningful to measure the abundance on site, an abundance-based currency using either directly observable or proxy indicators is the most representative measure of the net impact on the species. In other instances, such as when species are difficult to locate, or not reliably present on site, a currency based on the quality and amount of habitat is preferable. The habitat-quality component should be measured relative to its value for the species, with the most important attributes weighted accordingly. Ensuring the currency used in biodiversity offset transactions is practical to measure, and relevant to the species or vegetation community is an important step in minimising the net biodiversity losses from unavoidable impacts.

Evaluating Molecular Xenomonitoring as a Tool for Lymphatic Filariasis Surveillance in Samoa, 2018-2019.

Molecular xenomonitoring (MX), the detection of filarial DNA in mosquitoes using molecular methods (PCR), is a potentially useful surveillance strategy for lymphatic filariasis (LF) elimination programs. Delay in filarial antigen (Ag) clearance post-treatment is a limitation of using human surveys to provide an early indicator of the impact of mass drug administration (MDA), and MX may be more useful in this setting. We compared prevalence of infected mosquitoes pre- and post-MDA (2018 and 2019) in 35 primary sampling units (PSUs) in Samoa, and investigated associations between the presence of PCR-positive mosquitoes and Ag-positive humans. We observed a statistically significant decline in estimated mosquito infection prevalence post-MDA at the national level (from 0.9% to 0.3%, OR 0.4) but no change in human Ag prevalence during this time. Ag prevalence in 2019 was higher in randomly selected PSUs where PCR-positive pools were detected (1.4% in ages 5-9; 4.8% in ages ≥10), compared to those where PCR-positive pools were not detected (0.2% in ages 5-9; 3.2% in ages ≥10). Our study provides promising evidence for MX as a complement to human surveys in post-MDA surveillance.

A Bayesian network analysis quantifying risks versus benefits of the Pfizer COVID-19 vaccine in Australia.

The Pfizer COVID-19 vaccine is associated with increased myocarditis incidence. Constantly evolving evidence regarding incidence and case fatality of COVID-19 and myocarditis related to infection or vaccination, creates challenges for risk-benefit analysis of vaccination. Challenges are complicated further by emerging evidence of waning vaccine effectiveness, and variable effectiveness against variants. Here, we build on previous work on the COVID-19 Risk Calculator (CoRiCal) by integrating Australian and international data to inform a Bayesian network that calculates probabilities of outcomes for the delta variant under different scenarios of Pfizer COVID-19 vaccine coverage, age groups (≥12 years), sex, community transmission intensity and vaccine effectiveness. The model estimates that in a population where 5% were unvaccinated, 5% had one dose, 60% had two doses and 30% had three doses, there was a substantially greater probability of developing (239-5847 times) and dying (1430-384,684 times) from COVID-19-related than vaccine-associated myocarditis (depending on age and sex). For one million people with this vaccine coverage, where transmission intensity was equivalent to 10% chance of infection over 2 months, 68,813 symptomatic COVID-19 cases and 981 deaths would be prevented, with 42 and 16 expected cases of vaccine-associated myocarditis in males and females, respectively. These results justify vaccination in all age groups as vaccine-associated myocarditis is generally mild in the young, and there is unequivocal evidence for reduced mortality from COVID-19 in older individuals. The model may be updated to include emerging best evidence, data pertinent to different countries or vaccines and other outcomes such as long COVID.

Bayesian Network Analysis of Lymphatic Filariasis Serology from Myanmar Shows Benefit of Adding Antibody Testing to Post-MDA Surveillance.

The elimination of lymphatic filariasis (LF) is achieved through repeated mass drug administration (MDA) of anti-filarial medications, which interrupts transmission and prevents new infections. Accurate transmission assessments are critical to deciding when to stop MDA. Current methods for evaluating transmission may be insufficiently sensitive, resulting in post-MDA resurgence. We, therefore, evaluated potential diagnostic testing scenarios for post-MDA surveillance. Data were used from two surveys (a household cluster and a cohort) conducted in an area of Mandalay Region, Myanmar, with ongoing transmission following several rounds of MDA. First, age- and sex-adjusted seroprevalence were estimated for the area using the household survey. Next, three Bayesian networks were built from the combined datasets to compare antigens by immunochromatic testing (ICT) and/or Og4C3 enzyme-linked immunosorbent assay (ELISA) and antibody (Ab) detection methods (Wb123 or Bm14 Ab ELISA). The networks were checked for validity and then used to compare diagnostic testing scenarios. The adjusted prevalence from the household survey for antigen, Wb123 Ab and Bm14 Ab were 4.4% (95% CI 2.6-7.3%), 8.7% (5.96-12.5%) and 20.8% (16.0-26.6%), respectively. For the three networks, the True Skill Statistic and Area Under the Receiver Operating Characteristic Curve for antigen, Wb123 and Bm14 Ab were 0.79, 0.68 and 0.55; and 0.97, 0.92 and 0.80, respectively. In the Bayesian network analysis, a positive case was defined as testing positive to one or more infection markers. A missed result was therefore the probability of a positive case having a negative test result to an alternate marker. The probability of a positive case prior to any testing scenario was 17.4%, 16.8% and 26.6% for antigen, Wb123 Ab and Bm14 Ab, respectively. In the antigen-only testing scenario, the probability of a missed positive LF result was 5.2% for Wb123 and 15.6% for Bm14 Ab. The combination of antigen plus Bm14 Ab testing reduced the probability of missing a positive LF case as measured by Wb123 Ab to 0.88%. The combination of antigen plus Wb123 Ab was less successful and yielded an 11.5% probability of a missed positive result by Bm14 Ab testing. Across scenarios, there was a greater discordance between Bm14 and both antigen and Wb123 Ab in the 1-10 age group compared to older ages. These findings suggest that the addition of Bm14 Ab improves the sensitivity of LF testing for current or past infection. The combination of antigen plus Bm14 Ab should therefore be considered for inclusion in post-MDA surveillance to improve the sensitivity of transmission surveys and prevent the premature cessation of MDA.

Designing an evidence-based Bayesian network for estimating the risk versus benefits of AstraZeneca COVID-19 vaccine.

Uncertainty surrounding the risk of developing and dying from Thrombosis and Thrombocytopenia Syndrome (TTS) associated with the AstraZeneca (AZ) COVID-19 vaccine may contribute to vaccine hesitancy. A model is urgently needed to combine and effectively communicate evidence on the risks versus benefits of the AZ vaccine. We developed a Bayesian network to consolidate evidence on risks and benefits of the AZ vaccine, and parameterised the model using data from a range of empirical studies, government reports, and expert advisory groups. Expert judgement was used to interpret the available evidence and determine the model structure, relevant variables, data for inclusion, and how these data were used to inform the model. The model can be used as a decision-support tool to generate scenarios based on age, sex, virus variant and community transmission rates, making it useful for individuals, clinicians, and researchers to assess the chances of different health outcomes. Model outputs include the risk of dying from TTS following the AZ COVID-19 vaccine, the risk of dying from COVID-19 or COVID-19-associated atypical severe blood clots under different scenarios. Although the model is focused on Australia, it can be adapted to international settings by re-parameterising it with local data. This paper provides detailed description of the model-building methodology, which can be used to expand the scope of the model to include other COVID-19 vaccines, booster doses, comorbidities and other health outcomes (e.g., long COVID) to ensure the model remains relevant in the face of constantly changing discussion on risks versus benefits of COVID-19 vaccination.