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Objectives: Gonorrhoea caused by Neisseria gonorrhoeae is the second most notified sexually transmitted infection (STI) in Australia and the case numbers for this STI have been increasing globally. Progressive gonococcal infection may lead to disseminated gonococcal infection (DGI), which causes significant morbidity among patients. This study aims to examine the genetic diversity of N. gonorrhoeae isolates collected in Queensland from January 2010 to August 2015 and to determine factors associated with DGI in Queensland., Design: Retrospective surveillance study for epidemiological purposes., Setting: All gonorrhoeae isolates referred by private and public pathology laboratories to the state of Queensland, Australia Neisseria reference laboratory., Methods: Between January 2010 and August 2015, 3953 N. gonorrhoeae isolates from both metropolitan and regional Queensland infections were typed with NG-MAST ( N. gonorrhoeae multiantigen sequence typing) to assess the genetic diversity between strains. Whole-genome sequencing (WGS) was used to investigate strain-related factors associated with DGI., Results: ST6876 was the most common NG-MAST type, detected in 7.6% of the isolates. DGI was significantly more likely in females <30 years (OR 13.02, p<0.0001) and in older males >30 years (OR 6.04, p<0.0001), with most cases originating from North Queensland (OR 8.5, p<0.0001). Strains harbouring PIA class of porB type were associated with DGI (OR 33.23, p<0.0001)., Conclusion: Genotyping techniques, such as NG-MAST and WGS, are proving instrumental in providing an insight into the population structure of N. gonorrhoeae , and genetic mechanisms of pathogenesis, such as for DGI., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Leptospirosis is a zoonotic disease prevalent throughout the world, but with particularly high burden in Oceania (including the Pacific Island Countries and Territories). Leptospirosis is endemic in Fiji, with outbreaks often occurring following heavy rainfall and flooding. As a result of non-specific clinical manifestation and diagnostic challenges, cases are often misdiagnosed or under-ascertained. Furthermore, little is known about the duration of persistence of antibodies to leptospirosis, which has important clinical and epidemiological implications., Methodology and Principal Findings: Using the results from a serosurvey conducted in Fiji in 2013, we fitted serocatalytic models to estimate the duration of antibody positivity and the force of infection (FOI, the rate at which susceptible individuals acquire infection or seroconversion), whilst accounting for seroreversion. Additionally, we estimated the most likely timing of infection. Using the reverse catalytic model, we estimated the duration of antibody persistence to be 8.33 years (4.76-12.50; assuming constant FOI) and 7.25 years (3.36-11.36; assuming time-varying FOI), which is longer than previous estimates. Using population age-structured seroprevalence data alone, we were not able to distinguish between these two models. However, by bringing in additional longitudinal data on antibody kinetics we were able to estimate the most likely time of infection, lending support to the time-varying FOI model. We found that most individuals who were antibody-positive in the 2013 serosurvey were likely to have been infected within the previous two years, and this finding is consistent with surveillance data showing high numbers of cases reported in 2012 and 2013., Conclusions: This is the first study to use serocatalytic models to estimate the FOI and seroreversion rate for Leptospira infection. As well as providing an estimate for the duration of antibody positivity, we also present a novel method to estimate the most likely time of infection from seroprevalence data. These approaches can allow for richer, longitudinal information to be inferred from cross-sectional studies, and could be applied to other endemic diseases where antibody waning occurs., Competing Interests: The authors have declared that no competing interests exist.

Japanese encephalitis (JE) is the leading cause of viral encephalitis in Asia. Until 2022, only six locally transmitted human JE cases had been reported in Australia; five in northern Queensland and one in the Northern Territory. Thus, JE was mainly considered to be a disease of travellers. On 4 March 2022, JE was declared a 'Communicable Disease Incident of National Significance' when a locally acquired human case was confirmed in southern Queensland. By 11 May 2022, 41 human JE cases had been notified in four states in Australia, in areas where JE has never been detected before. From this perspective, we discuss the potential reasons for the recent emergence of the JE virus in Australia in areas where JE has never been previously reported as well as the implications of and options for mass immunisation programs if the outbreak escalates in a JE virus-immunologically naïve population.

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Containing antimicrobial resistance and reducing high levels of antibiotic consumption in low- and lower middle-income countries are a major challenge. Clinical guidelines targeting antibiotic prescribing can reduce consumption, however, the degrees to which clinical guidelines are adopted and adhered to are challenging for developers, policy makers and users. The aim of this study was to review the strategies used for implementing and promoting antibiotic guideline adherence in low- and lower middle-income countries. A review of published literature was conducted using PubMed, Cochrane Library, SCOPUS and the information systems of the World Health Organization and the Australian National University according to PRISMA guidelines and our PROSPERO protocol. The strategies were grouped into five broad categories based on the Cochrane Effective Practice and Organization of Care taxonomy. The 33 selected studies, representing 16 countries varied widely in design, setting, disease focus, methods, intervention components, outcomes and effects. The majority of interventions were multifaceted and resulted in a positive direction of effect. The nature of the interventions and study variability made it impossible to tease out which strategies had the greatest impact on improving CG compliance. Audit and feedback coupled with either workshops and/or focus group discussions were the most frequently used intervention components. All the reported strategies are established practices used in antimicrobial stewardship programs in high-income countries. We recommend interrupted time series studies be used as an alternative design to pre- and post-intervention studies, information about the clinical guidelines be made more transparent, and prescriber confidence be investigated.

Circulating filarial antigen (Ag) prevalence, measured using rapid point-of-care tests, is the standard indicator used for monitoring and surveillance in the Global Program to Eliminate Lymphatic Filariasis. In 2015, the immunochromatographic test (ICT) was replaced with the filariasis test strip (FTS), which has higher reported sensitivity. Despite differences in sensitivity, no changes in recommended surveillance targets were made when the FTS was introduced. In 2016, we conducted lymphatic filariasis surveys in American Samoa using FTS, which found higher Ag prevalence than previous surveys that used ICT. To determine whether the increase was real, we assessed the concordance between FTS and ICT results by paired testing of heparinised blood from 179 individuals (63% FTS-positive). ICT had 93.8% sensitivity and 100% specificity for identifying FTS-positive persons, and sensitivity was not associated with age, gender, or presence of microfilariae. Based on these findings, if ICT had been used in the 2016 surveys, the results and interpretation would have been similar to those reported using FTS. American Samoa would have failed Transmission Assessment Survey (TAS) of Grade 1 and 2 children with either test, and community prevalence would not have been significantly different (4.1%, 95% CI, 3.3-4.9% with FTS vs. predicted 3.8%, 95%, CI: 3.1-4.6% with ICT).

Transmission of many infectious diseases depends on interactions between humans, animals, and the environment. Incorporating these complex processes in transmission dynamic models can help inform policy and disease control interventions. We identified 20 diseases involving environmentally persistent pathogens (ie, pathogens that survive for more than 48 h in the environment and can cause subsequent human infections), of which indirect transmission can occur from animals to humans via the environment. Using a systematic approach, we critically appraised dynamic transmission models for environmentally persistent zoonotic diseases to quantify traits of models across diseases. 210 transmission modelling studies were identified and most studies considered diseases of domestic animals or high-income settings, or both. We found that less than half of studies validated their models to real-world data, and environmental data on pathogen persistence was rarely incorporated. Model structures varied, with few studies considering the animal-human-environment interface of transmission in the context of a One Health framework. This Review highlights the need for more data-driven modelling of these diseases and a holistic One Health approach to model these pathogens to inform disease prevention and control strategies., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Zika virus (ZIKV) has caused large, brief outbreaks in isolated populations, however ZIKV can also persist at low levels over multiple years. The reasons for these diverse transmission dynamics remain poorly understood. In Fiji, which has experienced multiple large single-season dengue epidemics, there was evidence of multi-year transmission of ZIKV between 2013 and 2017. To identify factors that could explain these differences in dynamics between closely related mosquito-borne flaviviruses, we jointly fit a transmission dynamic model to surveillance, serological and molecular data. We estimate that the observed dynamics of ZIKV were the result of two key factors: strong seasonal effects, which created an ecologically optimal time of year for outbreaks; and introduction of ZIKV after this optimal time, which allowed ZIKV transmission to persist over multiple seasons. The ability to jointly fit to multiple data sources could help identify a similar range of possible outbreak dynamics in other settings.

Uncertainty regarding transmission pathways and control measures makes prompt presentation and diagnosis for Buruli ulcer critical. To examine presentation and diagnosis delays in Victoria, Australia, we conducted a retrospective study of 703 cases notified between 2011 and 2017, classified as residing in an endemic (Mornington Peninsula; Bellarine Peninsula; South-east Bayside and Frankston) or non-endemic area. Overall median presentation delay was 30 days (IQR 14-60 days), with no significant change over the study period ( p = 0.11). There were significant differences in median presentation delay between areas of residence ( p = 0.02), but no significant change over the study period within any area. Overall median diagnosis delay was 10 days (IQR 0-40 days), with no significant change over the study period ( p = 0.13). There were significant differences in median diagnosis delay between areas ( p < 0.001), but a significant decrease over time only on the Mornington Peninsula ( p < 0.001). On multivariable analysis, being aged <15 or >65 years; having non-ulcerative disease; and residing in the Bellarine Peninsula or South-East Bayside (compared to non-endemic areas) were significantly associated with shorter presentation delay. Residing in the Bellarine or Mornington Peninsula and being notified later in the study period were significantly associated with shorter diagnosis delay. To reduce presentation and diagnosis delays, awareness of Buruli ulcer must be raised with the public and medical professionals, particularly those based outside established endemic areas.

In this study, a spatially-explicit agent-based modelling framework GEOFIL was developed to predict lymphatic filariasis (LF) transmission dynamics in American Samoa. GEOFIL included individual-level information on age, gender, disease status, household location, household members, workplace/school location and colleagues/schoolmates at each time step during the simulation. In American Samoa, annual mass drug administration from 2000 to 2006 successfully reduced LF prevalence dramatically. However, GEOFIL predicted continual increase in microfilaraemia prevalence in the absence of further intervention. Evidence from seroprevalence and transmission assessment surveys conducted from 2010 to 2016 indicated a resurgence of LF in American Samoa, corroborating GEOFIL's predictions. The microfilaraemia and antigenaemia prevalence in 6-7-yo children were much lower than in the overall population. Mosquito biting rates were found to be a critical determinant of infection risk. Transmission hotspots are likely to disappear with lower biting rates. GEOFIL highlights current knowledge gaps, such as data on mosquito abundance, biting rates and within-host parasite dynamics, which are important for improving the accuracy of model predictions., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Leptospirosis is a global zoonotic disease that the transmission is driven by complex geographical and temporal variation in demographics, animal hosts and socioecological factors. This results in complex challenges for the identification of high-risk areas. Spatial and temporal epidemiological tools could be used to support leptospirosis control programs, but the adequacy of its application has not been evaluated. We searched literature in six databases including PubMed, Web of Science, EMBASE, Scopus, SciELO and Zoological Record to systematically review and critically assess the use of spatial and temporal analytical tools for leptospirosis and to provide general framework for its application in future studies. We reviewed 115 articles published between 1930 and October 2018 from 41 different countries. Of these, 65 (56.52%) articles were on human leptospirosis, 39 (33.91%) on animal leptospirosis and 11 (9.5%) used data from both human and animal leptospirosis. Spatial analytical (n = 106) tools were used to describe the distribution of incidence/prevalence at various geographical scales (96.5%) and to explored spatial patterns to detect clustering and hot spots (33%). A total of 51 studies modelled the relationships of various variables on the risk of human (n = 31), animal (n = 17) and both human and animal infection (n = 3). Among those modelling studies, few studies had generated spatially structured models and predictive maps of human (n = 2/31) and animal leptospirosis (n = 1/17). In addition, nine studies applied time-series analytical tools to predict leptospirosis incidence. Spatial and temporal analytical tools have been greatly utilized to improve our understanding on leptospirosis epidemiology. Yet the quality of the epidemiological data, the selection of covariates and spatial analytical techniques should be carefully considered in future studies to improve usefulness of evidence as tools to support leptospirosis control. A general framework for the application of spatial analytical tools for leptospirosis was proposed., (© 2018 Blackwell Verlag GmbH.)

Population mobility has been demonstrated to contribute to the persistent transmission and global diffusion of epidemics. In the Pacific Islands, population mobility is particularly important for emerging infectious diseases, disease elimination programs, and diseases spread by close contact. The extent of population mobility between American Samoa villages, Samoa districts and other countries was investigated based on travel data collected during community surveys in American Samoa in 2010 and 2014. Within American Samoa, workers commuted daily across the whole of the main island of Tutuila, with work hubs drawing from villages across the island. Of the 670 adult workers surveyed, 37% had traveled overseas in the past year, with 68% of trips to Samoa. Of children aged 8-13 years (n = 337), 57% had traveled overseas, with 55% of trips to Samoa. An extensive network of connections between American Samoa villages and Samoa districts was demonstrated, with most trips lasting one week to one month. Our study showed that populations in the Samoan islands are highly mobile, and quantified the extent and destinations of their travels. Our findings offer insight into the impact of population mobility on the transmission of infectious diseases and data to refine existing models of disease transmission in the Pacific islands.

Background: Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR) to provide insights into the ecoepidemiology of human leptospirosis in Fiji., Methods: We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1-90 years) was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month) on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR) for each covariate., Findings: The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but GWLR also detected spatial variation in the effect of each covariate. Maximum rainfall had the least variation across space (median OR 1·30, IQR 1·27-1·35), and distance to river varied the most (1·45, 1·35-2·05). The predictive risk map indicated that the highest risk was in the interior of Viti Levu, and the agricultural region and southern end of Vanua Levu., Interpretation: GWLR provided a valuable method for modelling spatial heterogeneity of covariates for leptospirosis infection and their relative importance over space. Results of GWLR could be used to inform more place-specific interventions, particularly for diseases with strong environmental or sociodemographic drivers of transmission., Funding: WHO, Australian National Health & Medical Research Council, University of Queensland, UK Medical Research Council, Chadwick Trust., (Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Leptospirosis is one of the most common zoonotic diseases worldwide. Infection occurs through contact with infected animals, or soil or water that has been contaminated by the urine of infected animals. Risk factors include occupational and recreational exposures, contact with floodwaters, and travel to areas with a high risk of leptospirosis, particularly tropical, developing countries. With climate change, flood-related outbreaks are becoming more common., Objective: This article aims to improve awareness of leptospirosis, and provide an update for general practitioners on its epidemiology, risk factors, clinical presentation, laboratory diagnosis, management and prevention., Discussion: Leptospirosis is sometimes misdiagnosed because clinical presentation can be non-specific and overlap with many other causes of acute febrile illnesses. In patients with risk factors for leptospirosis, a high index of clinical suspicion is important to ensure early diagnosis and treatment. Delays in treatment could increase the risk of severe complications, including pulmonary haemorrhage, acute renal failure and acute liver failure.

Recently the role of soil-transmitted helminth (STH) infections in children's cognitive developmental impairment has been under scrutiny. We conducted a systematic review of the evidence for associations between STH infections and cognitive function of children using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. We aimed to identify the domains of cognitive function in three age strata (<24months, 24-59months and ≥60months) and critically appraise the general design protocol of the studies, with a focus on the cognitive function measurement tools used. A total of 42 papers fulfilled the inclusion criteria, including 10 studies from a recent Cochrane review. Our findings demonstrate variation in tested domains, lack of consistency in the use of measurement tools and analysis of results. Cognitive function measures in children aged under 59months have been mainly limited to domains of gross motor, fine motor and language skills, whereas in children aged 60months and above most studies tested domains such as memory and processing speed. Even within the same age group the results on the association between STH infections and measures of cognitive development were often conflicting. The current study highlights the need for methodological consensus in the use of measurement tools and data analysis protocols if the effect of STH infections on cognitive function domains in children is to be correctly established. This will be an imperative next step to generate conclusive evidence of the role of STH infections in cognitive development in children., (Copyright © 2017 Elsevier Ltd. All rights reserved.)