Patterns Of Disease Prevalence Research Articles

Higher cardiovascular disease risks in people living with HIV: A systematic review and meta-analysis.

The prognosis of AIDS after active antiretroviral therapy (ART) and the quality of life of people living with HIV (PLWH) are both affected by non-AIDS-related diseases such as cardiovascular disease (CVD). However, the specific risk ratios between PLWH and individuals negative for HIV are poorly understood. We aimed to systematically review and investigate the CVD risk factors associated with HIV. We searched PubMed, Embase, Web of Science, and Cochrane Library databases between 1 January 2015, and 12 May 2023 for articles reported the prevalence and risk factors of CVD such as hypertension, dyslipidaemia, coronary artery disease (CAD), and myocardial infarction (MI). Due to the high heterogeneity, we used a random-effects model to analyse the data. All statistical analyses were performed using Stata/MP 17.0 with 95% confidence intervals (CIs). We analysed 31 eligible studies including 312 913 PLWH. People living with HIV had higher risks of dyslipidaemia (hazard ratio (HR) = 1.53; 95% CI = 1.29, 1.82), CAD (HR = 1.37; 95% CI = 1.24, 1.51), and MI (HR = 1.47; 95% CI = 1.28, 1.68) compared to individuals without HIV. However, there were no significant differences in the prevalence of hypertension between groups (HR = 1.17; 95% CI = 0.97, 1.41). Subgroup analysis revealed that men with HIV, PLWH who smoked and the elderly PLWH had a high prevalence of CVD. Moreover, the disease prevalence patterns varied among regions. In the USA and Europe, for instance, some HRs for CVD were higher than in other regions. Active ART initiation after 2015 appears to have a lower risk of CVD (hypertension, hyperlipidaemia, CAD). All outcomes under analysis showed significant heterogeneity (I2>70%, P < 0.001), which the available study-level variables could only partially account for. People living with HIV had a higher CVD risk than the general population; thus, CVD prevention in PLWH requires further attention. Rapid initiation of ART may reduce the incidence of CVD in PLWH. For timely screening of CVD high-risk individuals and thorough disease management to prevent CVD, further studies are required to evaluate the risk factors for CVD among PLWH, such as age, region, etc. PROSPERO (CRD42021255508).

The prevalence of rodent-borne zoonotic pathogens in the South Gobi desert region of Mongolia

ABSTRACT The alpine ecosystems and communities of central Asia are currently undergoing large-scale ecological and socio-ecological changes likely to affect wildlife-livestock-human disease interactions and zoonosis transmission risk. However, relatively little is known about the prevalence of pathogens in this region. Between 2012 and 2015 we screened 142 rodents in Mongolia’s Gobi desert for exposure to important zoonotic and livestock pathogens. Rodent seroprevalence to Leptospira spp. was >1/3 of tested animals, Toxoplasma gondii and Coxiella burnetii approximately 1/8 animals, and the hantaviruses being between 1/20 (Puumala-like hantavirus) and <1/100 (Seoul-like hantavirus). Gerbils trapped inside local dwellings were one of the species seropositive to Puumala-like hantavirus, suggesting a potential zoonotic transmission pathway. Seventeen genera of zoonotic bacteria were also detected in the faeces and ticks collected from these rodents, with one tick testing positive to Yersinia. Our study helps provide baseline patterns of disease prevalence needed to infer potential transmission between source and target populations in this region, and to help shift the focus of epidemiological research towards understanding disease transmission among species and proactive disease mitigation strategies within a broader One Health framework.

Screening Charity Recipients: Health Philanthropy, Medical Diagnosis, and Kidney Disease Prevention in Sri Lanka

Over the last several decades, epidemics of chronic kidney disease of unknown aetiology (CKDu) have appeared in Mesoamerica, North Africa, and South Asia. Drawing on 14 months of ethnographic fieldwork in a CKDu-affected village in Sri Lanka, I explore how one CKDu ‘hotspot’ came into being following population screening interventions by a community development organisation, a philanthropic foundation, and a university research group. While the production of test results proved vital to the mobilisation of further research and public health resources for the community, this ethnography reveals philanthropy could be seen to have shaped by screening as much as screening was seen to have influenced by philanthropy. The example of medical screening and philanthropic interventions in Ginnoruwa illustrates how bioindicators of failing kidney function became a key metric for demarcating the community into populations of the deserving (or not so deserving) poorly, which in turn helped to create the pattern of disease prevalence and concentration that led to the community being designated a ‘hotspot’. In Ginnoruwa, philanthropy and screening did not operate independently but constituted a novel hybrid, which I refer to as ‘philanthropic science’.

Population-Level Patterns of Prostate Cancer Occurrence: Disparities in Virginia.

Prostate cancer is the most common cancer and the second leading cause of cancer-related deaths among men in the United States. In Virginia, which is a representative, ethnically diverse state of more than 8 million people that was established nearly 400 years ago, prostate cancer has the highest rate of new detection for any type of cancer. All men are at risk of developing prostate cancer regardless of demographics, but some men have an increased mortality risk due to cancer metastasis. Notably, one in five African American men will be diagnosed with prostate cancer in their lifetime and they have the highest prostate cancer mortality rate of any ethnic group in the United States, including Virginia. A person's genetic profile and family history are important biological determinants of prostate cancer risk, but modifiable environmental factors (e.g., pollution) appear to be correlated with patterns of disease prevalence and risk. In this review, we examine current perspectives on population-level spatial patterns of prostate cancer in Virginia. For context, recent, publicly available data from the Centers for Disease Control and Prevention are highlighted and presented in spatial format. In addition, we explore possible co-morbidities of prostate cancer that may have demographic underpinnings highlighted in recent health disparity studies.

Variability in Global Prevalence of Interstitial Lung Disease.

There are limited epidemiologic studies describing the global burden and geographic heterogeneity of interstitial lung disease (ILD) subtypes. We found that among seventeen methodologically heterogenous studies that examined the incidence, prevalence and relative frequencies of ILDs, the incidence of ILD ranged from 1 to 31.5 per 100,000 person-years and prevalence ranged from 6.3 to 71 per 100,000 people. In North America and Europe, idiopathic pulmonary fibrosis and sarcoidosis were the most prevalent ILDs while the relative frequency of hypersensitivity pneumonitis was higher in Asia, particularly in India (10.7–47.3%) and Pakistan (12.6%). The relative frequency of connective tissue disease ILD demonstrated the greatest geographic variability, ranging from 7.5% of cases in Belgium to 33.3% of cases in Canada and 34.8% of cases in Saudi Arabia. These differences may represent true differences based on underlying characteristics of the source populations or methodological differences in disease classification and patient recruitment (registry vs. population-based cohorts). There are three areas where we feel addition work is needed to better understand the global burden of ILD. First, a standard ontology with diagnostic confidence thresholds for comparative epidemiology studies of ILD is needed. Second, more globally representative data should be published in English language journals as current literature has largely focused on Europe and North America with little data from South America, Africa and Asia. Third, the inclusion of community-based cohorts that leverage the strength of large databases can help better estimate population burden of disease. These large, community-based longitudinal cohorts would also allow for tracking of global trends and be a valuable resource for collective study. We believe the ILD research community should organize to define a shared ontology for disease classification and commit to conducting global claims and electronic health record based epidemiologic studies in a standardized fashion. Aggregating and sharing this type of data would provide a unique opportunity for international collaboration as our understanding of ILD continues to grow and evolve. Better understanding the geographic and temporal patterns of disease prevalence and identifying clusters of ILD subtypes will facilitate improved understanding of emerging risk factors and help identify targets for future intervention.

Complementary and Alternative Medicine (CAM): A Detailed Review

Background: India, because of its lavish cultural heritage is rich in its traditional knowledge of treatment of ailments in various forms for the maintenance of health as well as in the prevention, diagnosis, improvement or treatment of physical and mental illness. Objective: India having vast ethnic variability, has different disease prevalence patterns. Therefore an attempt has been made to review the practice of different systems of medicines or CAM. Material and Methods: All other forms of treatments (regarded as complementary or alternative medicine) such as homeopathy, herbal therapy, acupuncture, acupressure, magnet, massage, yoga, naturopathy, mud, aroma, colour and gem therapy have been reviewed in detail for its literature available from the various sources. Result: CAM in the form of therapies can also be organized into different categories, which provides safer solution to various complications in the utmost gentle manner. Conclusion: The future prospects of CAM are very promising in India and the need is to study out and implement these systems of medicine in a systemic and planned way.

A forecasting model of disease prevalence based on the McKendrick–von Foerster equation

A new model for disease prevalence based on the analytical solutions of McKendric–von Foerster's partial differential equations is developed. Derivation of the model and methods to cross check obtained results are explicitly demonstrated. Obtained equations describe the time evolution of the healthy and unhealthy age-structured sub-populations and age patterns of disease prevalence. The projection of disease prevalence into the future requires estimates of time trends of age-specific disease incidence, relative survival functions, and prevalence at the initial age and year available in the data. The computational scheme for parameter estimations using Medicare data, analytical properties of the model, application for diabetes prevalence, and relationship with partitioning models are described and discussed. The model allows natural generalization for the case of several diseases as well as for modeling time trends in cause-specific mortality rates.

PHARMACOVIGILANCE: DYNAMICS IN INDIAN PHARMA INDUSTRY

Pharmacovigilance refers to the process of identifying, detecting, and responding to drug safety issue and has witnessed dynamic advancements in pharmaceutical industries throughout the world. The main objective of pharmacovigilance is to extend the safety monitoring and to detect any ADRs that previously got unrecognized in evolution during clinical trial. ADRs monitoring is required for each medicine throughout its lifecycle which includes early stage of drug design, clinical trials, and post marketing surveillance. The emerging trend in pharmacovigilance is to link the pre marketing data with the data collected during post marketing phase that include safety information. India is a vast country with population of over 1.32 Billion with different social economics status, different patterns of disease prevalence it becomes more important to have a standardized and robust pharmacovigilance. Pharmacists, as doctor remark that their involvement may increase the reporting rate and have a greater role to play in the area of pharmacovigilance

Seasonal variation in the number of deaths in Pteropus lylei at Wat Pho Bang Khla temple, Thailand.

Flying foxes have been widely studied as they are well-known reservoirs of infectious agents. Understanding their population dynamics might help to explain seasonal patterns of disease prevalence, and contribute towards the conservation of flying fox populations. Therefore, this study explored the annual variation in the number of deaths in P. lylei. The study was conducted from 2015–2017, at a Buddhist temple in Thailand, which is the roosting site of P. lylei. The average total number of bat deaths in a month significantly varied between times of a year. A peak was observed during March and May, which ranged in the period of birthing and lactating. There were no significant differences in the average total number of bat deaths in a month between sexes or age classes across times of a years.

The association of lower urinary tract symptoms with incidental falls and fear of falling in later life: The Community Health Survey.

To evaluate the association between lower urinary tract symptoms (LUTS) and incidental falls and fear of falling. We used data obtained from the 2011 Korean Community Health Survey (KCHS) conducted between August and October 2011 in South Korea. The survey was carried out to estimate patterns of disease prevalence and morbidity in men >40 years old. The trained interviewers performed face-to-face sociodemographic questionnaires using computer-assisted personal interviewing (CAPI) software, the International Prostate Symptom Score (IPSS), the Quality of Life score (EQ-5D), and a questionnaire about past falls and fear of falling. Data from 67 457 men were collected and analyzed. The subjects who had previously experienced a fall had slightly higher scores for IPSS, severity of LUTS, voiding LUTS, and storage LUTS than subjects with no prior fall history. A multivariate model of the relationship between falls and LUTS severity indicated that the relationship between the IPSS components and fall history was significant (mild, moderate, severe: OR = 1.00, 2.53, 3.91, respectively, P < 0.0001). A multivariate model of fear of falling and LUTS also showed a significant relationship between severity, voiding, and storage symptoms (severe IPSS: OR = 2.411, 95%CI: 2.2-2.642, P < 0.001; voiding symptoms: OR = 1.766, 95%CI: 1.681-1.856, P < 0.001; storage symptoms: OR = 1.705, 95%CI: 1.625-1.789, P < 0.001). This study emphasizes the relationship between LUTS and falling. Furthermore, increased LUTS severity led to a higher risk of incidental falls. A high correlation between fear of falling and LUTS was also observed in this study.

Some coral diseases track climate oscillations in the Caribbean

Disease outbreaks continue to reduce coral populations worldwide. Understanding coral diseases and their relationships with environmental drivers is necessary to forecast disease outbreaks, and to predict future changes in coral populations. Yet, the temporal dynamics of coral diseases are rarely reported. Here we evaluate trends and periodicities in the records of three common coral diseases (white-band disease, yellow-band disease, and dark-spot syndrome) that were surveyed between 1997 and 2014 at 2082 sites throughout the Caribbean. The relationship between the periodicities of disease prevalence and El Niño Southern Oscillation (ENSO) cycles was examined using cross-wavelet analyses and convergent cross mapping (CCM). The prevalence of the diseases peaked every two to four years, and matched periodicities in ENSO conditions. CCM models suggested that environmental conditions associated with recent ENSO cycles may have influenced the patterns in disease prevalence. We also found no increasing trends in disease prevalence through time. Instead, our work suggests that the prevalence of coral diseases is dynamic and complex. The gradual increase in sea-surface temperature, a consequence of increasing greenhouse gas emissions, progressively raises the modal temperature threshold of each ENSO cycle. These dynamic cycles and the increasing modal temperatures appear to influence the dynamics of coral diseases.

Coral disease hotspots in the Caribbean

AbstractRecent outbreaks of coral diseases in the Caribbean have been linked to increasingly stressful sea‐surface temperatures (SSTs). Yet, ocean warming is spatially heterogeneous and therefore has the potential to lead to hotspots of disease activity. Here, we take an epidemiological approach to examine spatial differences in the risk of white‐band disease on Acropora spp. and yellow‐band disease on Orbicella spp. in the Caribbean. Our analysis involved examining the spatial patterns of disease prevalence, and creating a Bayesian‐risk model that tested for regional differences in disease risk. The spatial examination of disease prevalence showed several clusters of white‐band disease, including high prevalence in the Turks and Caicos, Jamaica, Puerto Rico, the Virgin Islands, and Belize, whereas yellow‐band disease seemed most prevalent along the Yucatan Peninsula. The Bayesian‐risk model showed regional clusters of white‐band disease near the southern Dominican Republic, Puerto Rico, the Virgin Islands, and the Lesser Antilles, whereas the risk of yellow‐band disease was highest in the southern Caribbean. The relative risk of both diseases increased with warmer SSTs. The Bayesian‐risk model allowed us to predict where we should expect future outbreaks of coral diseases at a regional scale, and suggests regions where the implementation of disease mitigation plans may be most urgent.

RISK FACTORS FOR AND SPATIAL DISTRIBUTION OF LYMPHOPROLIFERATIVE DISEASE VIRUS (LPDV) IN WILD TURKEYS (MELEAGRIS GALLOPAVO) IN NEW YORK STATE, USA.

Lymphoproliferative disease virus (LPDV) is an oncogenic avian retrovirus that was previously thought to exclusively infect domestic turkeys but was recently shown to be widespread in Wild Turkeys ( Meleagris gallopavo ) throughout most of the eastern US. In commercial flocks, the virus spreads between birds housed in close quarters, but there is little information about potential risk factors for infection in wild birds. Initial studies focused on distribution of LPDV nationally, but investigation of state-level data is necessary to assess potential predictors of infection and detect patterns in disease prevalence and distribution. We tested wild turkey bone marrow samples (n=2,538) obtained from hunter-harvested birds in New York State from 2012 to 2014 for LPDV infection. Statewide prevalence for those 3 yr was 55% with a 95% confidence interval (CI) of 53-57%. We evaluated a suite of demographic, anthropogenic, and land cover characteristics with logistic regression to identify potential predictors for infection based on odds ratio (OR). Age (OR=0.16, 95% CI=0.13-0.19) and sex (OR=1.3, 95% CI=1.03-1.24) were strong predictors of LPDV infection, with juveniles less likely to test positive than adults, and females more likely to test positive than males. The number of birds released during the state's 40-yr translocation program (OR=0.993, 95% CI=0.990-0.997) and the ratio of agriculture to forest cover (OR=1.13, 95% CI=1.03-1.19) were also predictive of LPDV infection. Prevalence distribution was analyzed using dual kernel density smoothing to produce a risk surface map, combined with Kulldorff's spatial scan statistic and the Anselin Local Moran's I to identify statistically significant geographic clusters of high or low prevalence. These methods revealed the prevalence of LPDV was high (>50%) throughout New York State, with regions of variation and several significant clusters. We revealed new information about the risk factors and distribution of LPDV in New York State, which may be beneficial to game bird managers and producers of organic or pasture-raised poultry.

Significant decline in anticancer immune capacity during puberty in the Tasmanian devil

Tasmanian devils (Sarcophilus harrisii) are at risk of extinction in the wild due to Devil Facial Tumour Disease (DFTD), a rare contagious cancer. The prevalence of DFTD differs by age class: higher disease prevalence is seen in adults (2–3 years) versus younger devils (<2 years). Here we propose that immunological changes during puberty may play a role in susceptibility to DFTD. We show that the second year of life is a key developmental period for Tasmanian devils, during which they undergo puberty and pronounced changes in the immune system. Puberty coincides with a significant decrease in lymphocyte abundance resulting in a much higher neutrophil:lymphocyte ratio in adults than subadults. Quantitative PCR analysis of gene expression of transcription factors T-bet and GATA-3 and cytokines interferon gamma (IFN-γ) and interleukin 4 (IL-4) revealed a drastic increase in GATA-3 and IL-4 expression during puberty. These changes led to a significantly lower IFN-γ:IL-4 ratio in 2-year-olds than <1 year olds (on average 1.3-fold difference in males and 4.0-fold in females), which reflects a major shift of the immune system towards Th2 responses. These results all indicate that adult devils are expected to have a lower anticancer immune capacity than subadults, which may explain the observed pattern of disease prevalence of DFTD in the wild.

Local demographic and epidemiological patterns in the Linum marginale–Melampsora lini association: a multi‐year study

Summary Many theoretical and empirical studies operate from an assumption that pathogens have a significant influence on the fecundity and life span of their host species. However, there are surprisingly little data investigating the long‐term fitness impacts and genetic consequences that arise from pathogen infection in natural populations. Here, we address this gap through the analysis of a dataset investigating the local population dynamics of a native host plant (Linum marginale) and an associated rust pathogen (Melampsora lini) across 12 years. To investigate patterns of disease prevalence and severity and track effects on host fecundity and demography, we conducted censuses on an annual basis at a single site. Annual M. lini infection prevalence ranged from 0% to 99%. Severe epidemics occurred in 3‐ to 4‐year cycles causing high overwintering mortality and subsequent changes in the relative abundance of different host phenotypes. Host population size oscillated in response to epidemics and declined towards the end of the observation period. Changes in host numbers were found to affect disease severity but not infection prevalence. Melampsora lini infection increased L. marginale fecundity; the infected plants produced threefold more seed capsules on average than uninfected plants (13·3 vs. 4·3 seed capsules per plant). To investigate how variation in environmental conditions affects epidemiology and host demography, we identified climatic factors affecting host growth, overwintering and disease severity. Winter (June) rainfall increased host overwintering success and summer (December) rainfall favoured host growth. The progress of M. lini disease epidemics benefited from optimal temperatures in February and suffered from rainfall in January. We further examined links between the genetic structure of the pathogen population and disease dynamics. There was a positive correlation between mean pathogen infectivity (as measured across a host differential set) and the severity of disease epidemics. Synthesis. Our results provide new insights into local drivers and consequences of pathogen epidemiology in natural populations. Melampsora lini infection can have profound consequences on the phenotype, demography and population structure of Linum marginale by increasing host fecundity, overwinter mortality and disease resistance.

Evolutionary triangulation: informing genetic association studies with evolutionary evidence.

Genetic studies of human diseases have identified many variants associated with pathogenesis and severity. However, most studies have used only statistical association to assess putative relationships to disease, and ignored other factors for evaluation. For example, evolution is a factor that has shaped disease risk, changing allele frequencies as human populations migrated into and inhabited new environments. Since many common variants differ among populations in frequency, as does disease prevalence, we hypothesized that patterns of disease and population structure, taken together, will inform association studies. Thus, the population distributions of allelic risk variants should reflect the distributions of their associated diseases. Evolutionary Triangulation (ET) exploits this evolutionary differentiation by comparing population structure among three populations with variable patterns of disease prevalence. By selecting populations based on patterns where two have similar rates of disease that differ substantially from a third, we performed a proof of principle analysis for this method. We examined three disease phenotypes, lactase persistence, melanoma, and Type 2 diabetes mellitus. We show that for lactase persistence, a phenotype with a simple genetic architecture, ET identifies the key gene, lactase. For melanoma, ET identifies several genes associated with this disease and/or phenotypes related to it, such as skin color genes. ET was less obviously successful for Type 2 diabetes mellitus, perhaps because of the small effect sizes in known risk loci and recent environmental changes that have altered disease risk. Alternatively, ET may have revealed new genes involved in conferring disease risk for diabetes that did not meet nominal GWAS significance thresholds. We also compared ET to another method used to filter for phenotype associated genes, population branch statistic (PBS), and show that ET performs better in identifying genes known to associate with diseases appropriately distributed among populations. Our results indicate that ET can filter association results to improve our ability to discover disease loci.Electronic supplementary materialThe online version of this article (doi:10.1186/s13040-016-0091-7) contains supplementary material, which is available to authorized users.

Explaining provincial disease network via graph-theoretic analysis of disease occurrence in Iran

PurposeSocial networks are increasingly being used to study the epidemiology of human diseases. These methods are usually limited to studying a single or a small group of diseases within a small community and may not fully capture effects of environmental factors that drift the epidemiology of diseases at the community level (rather than individual level). By introducing an ecological variant of the social network, we described provincial disease network (PDN) to study the similarities in regional occurrence of diseases. MethodsIn this network, nodes (provinces) are connected via edges together. Provinces that have similar pattern of disease prevalence and/or incidence tie stronger together. We sought to find modular organization of Iran's PDN and to identify factors (literacy, rural population percentage, smoking, geographical distance, and age distribution) that could predict the strength of interprovincial connections in the PDN. ResultsProvinces in Iran's PDN were segregated into five different modules. Geographic distance, differences in the literacy percentage and percentage of population in the 0–16 years age group showed significant inverse correlation with strength of connections in Iran's PDN. ConclusionsNetwork-based approaches could provide important insights by identifying modular architecture within the PDN and underlying factors that drive similarity between disease patterns among regional entities.

Leading indicators of mosquito-borne disease elimination.

Mosquito-borne diseases contribute significantly to the global disease burden. High-profile elimination campaigns are currently underway for many parasites, e.g., Plasmodium spp., the causal agent of malaria. Sustaining momentum near the end of elimination programs is often difficult to achieve and consequently quantitative tools that enable monitoring the effectiveness of elimination activities after the initial reduction of cases has occurred are needed. Documenting progress in vector-borne disease elimination is a potentially important application for the theory of critical transitions. Non-parametric approaches that are independent of model-fitting would advance infectious disease forecasting significantly. In this paper, we consider compartmental Ross-McDonald models that are slowly forced through a critical transition through gradually deployed control measures. We derive expressions for the behavior of candidate indicators, including the autocorrelation coefficient, variance, and coefficient of variation in the number of human cases during the approach to elimination. We conducted a simulation study to test the performance of each summary statistic as an early warning system of mosquito-borne disease elimination. Variance and coefficient of variation were highly predictive of elimination but autocorrelation performed poorly as an indicator in some control contexts. Our results suggest that tipping points (bifurcations) in mosquito-borne infectious disease systems may be foreshadowed by characteristic temporal patterns of disease prevalence.

Bridging the Healthcare Access Divide: A Strategic Planning Model for Rural Telemedicine Network

ABSTRACTBalancing access to healthcare and sustaining operational efficiency is a major issue in strategic planning of rural healthcare delivery systems. In this regard, telemedicine is being adopted as a versatile and low cost mechanism for delivering rural healthcare. This article presents a strategic planning model that incorporates different operational and service elements of the rural telemedicine healthcare network. Real‐world data from the rural Black‐belt region in the United States are used in a case study. A novel statistical approach based on decision trees and logistic regression is used to estimate demand of healthcare at the county level. Key issues such as the location of telemedicine health centers, coverage of health services, configuration of medical equipment, and patient travel policies are explored in light of patient demographics, scale of health coverage, and disease prevalence patterns. Results indicate that telemedicine networks can effectively improve healthcare services in rural areas with requisite operational efficiency.

Distribution of the disease pathogen Batrachochytrium dendrobatidis in non‐epidemic amphibian communities of western Canada

Chytridiomycosis is an emerging infectious disease of amphibians caused by the waterborne pathogen Batrachochytrium dendrobatidis (Bd) and is responsible for the recent decline of species worldwide. Elucidating patterns in disease prevalence has proved challenging, as small‐scale studies to date have provided conflicting results. We present data on the prevalence of Bd (the proportion of individuals with Bd) collected from amphibians sampled throughout British Columbia. We had two different datasets: our original dataset includes 1129 individuals sampled in 103 sites representing 14 species. A second dataset has 839 individuals sampled in 19 sites representing 10 species. We use a Bayesian state‐space occupancy modelling approach to estimate the probability that an individual is Bd+ as a function of individual and site characteristics. Cross‐validation techniques and the original dataset were used to find the best model: this model includes species, life stage, and geographic location. Our results suggest that Bd prevalence is not strongly related to seasonality, latitude or site type. Within a species, Bd prevalence depended on life stage; the watershed in which a site occurs may also usefully predict prevalence. Overall observed infection prevalence was ∼16%. Our best model accurately assigns Bd status to an individual ∼ 42% of the time. Taking advantage of the Bayesian framework, we ran an analysis with the second dataset using estimates from the original model as prior values. We present posterior density distributions for those sites and species with narrow credible intervals, and show that sites tend to be either highly likely or highly unlikely to have individuals with Bd, while individuals of some stages of some species have an intermediate likelihood of being Bd‐positive. The Bayesian model using informed priors had increased accuracy rates in assigning Bd status to both individuals and groups of individuals.