bayesian analysis

 Exploring the pattern of diseases in space and time enhances our understanding of truly needy areas. The present study aimed to explore spatiotemporal mapping of colorectal cancer (CRC) and gastric cancer (GC) incidence using Bayesian models and space-time scan statistics in Hamadan Province from 2010 to 2019.

Study Design: 

An ecological time-series study.

 In this study, the data on CRC and GC cases were obtained from Hamadan cancer registry. The crude standardized incidence ratio (SIR) was calculated for each county per year. Hierarchical Bayesian space-time models were fitted to estimate adjusted SIRs. Space time cluster analysis was performed using space-time scan statistic.

 A total of 1864 CRC cases and 2340 GC cases were included in the analyses. The central counties, including Hamadan (smoothed SIR range: 1.24-1.28) and Tuyserkan (1.01-1.24), exhibited higher than expected number of CRC cases. Northern counties such as Razan (1.19-1.51) and Kabudarahang (1.21-1.42), along with Nahavand in the south (0.98, 1.53), also showed higher than expected number of GC cases. The most likely spatiotemporal cluster of CRC was identified in Hamadan and Tuyserkan occurring between 2015 and 2019 (relative risk [RR]=1.82, P<0.001). The most likely spatiotemporal cluster of GC was identified in Nahavand from 2010 to 2011 (RR=1.87, P<0.001).

 Spatiotemporal inequality in the incidence of CRC and GC was identified in Hamadan province over the past decade. The findings may help to reduce cancer disparities and allocate effective resources in the appropriate region and time in the future.

Prostate cancer is an emerging health problem in Sub-Saharan Africa and it is often diagnosed at an advanced stage due to the lack of access to screening and diagnostic facilities.

This study therefore aimed at modelling the effects of risk factors on the outcome of prostate cancer screening using Generalized Bayesian ordinal logistic regression with random effects then compare the results obtained with the model without random effects. The study further used Mean Squared Errors and established that the estimates for the two models were different

The findings in this study indicate that aged individuals have high chances of having prostate cancer at the early, late or advanced stage. The individual with traces of family history and hereditary breast & ovarian cancer syndrome are also most likely to be in late or advanced stage of prostate cancer.

From the findings aged individuals, having traces of family history and individuals with hereditary breast & ovarian cancer history, should be on alert and understand all symptoms of prostate cancer. For any signs or appearance of prostate cancer symptoms, they are supposed seek for screening services at earliest time possible. In addition, the Ministry of Health should create awareness training and increase screening facilities, this will also encourage for early screening and detection of prostate cancer. The different estimates led to identifying the best model, whereby models with presence of random effects had lowest Widely Applicable Information Criterion values hence they were considered to be the best models in each category.

The HIV Sentinel Surveillance (HSS) conducted by National AIDS Control Organization (NACO) is the predominant data source for HIV estimations in India. While the HSS targets the key populations at risk of HIV infection, the National Family Health Survey (NFHS) measures the communitybased HIV prevalence. Improvised HIV estimates in India were attributed to the HIV prevalence data obtained from the NACO-HSS and NFHS.

Bayesian analysis was performed to determine the state-level prevalence of HIV among females in seven South Indian States. The analysis involved plotting the prior, likelihood, and posterior distributions, facilitating a visual assessment of the data. The HIV prevalence among females calculated from the NFHS (2015-16) survey data was used for prior distributions. HIV prevalence among pregnant women obtained from the HIV Sentinel Surveillance 2019 was used for likelihood. Bayesian analysis was performed using the R programming (RStudio 2022.02.0). A posterior probability distribution was obtained using the prior distribution and the likelihood by applying the Bayes theorem. Graphical representation was achieved through R's plotting functions. Kerala and Pondicherry were not included in the analysis due to zero or very low prevalence reported in both NFHS and HSS.

The Bayesian estimates of HIV prevalence among females were 0.38 % [95% CI:0.29 - 0.47] in Andhra Pradesh, 0.28 [95% CI:0.23 - 0.35] in Karnataka, 0.27 [95% CI:0.20 - 0.34] Odisha, 0.27 % [95% CI:0.19 - 0.36] in Telangana and 0.19 [95% CI:0.15 - 0.24] in Tamil Nadu.

Bayesian techniques present a versatile and robust strategy for modelling and analysing HIVrelated data, offering a flexible and powerful approach to data analysis.

Bipolar I disorder is one of the most frequent mental disorders characterized by manic or mixed +/- depressive episodes. Drug treatment has been proved to diminish next episodes, but many other factors are important for exacerbating the conditions. This study aimed to investigate the effective factors on the time and number of episodes in these patients by applying the shared frailty model.

In this retrospective longitudinal study, the information of 606 patients with bipolar I disorder, admitted for the first time in Ibn-e-Sina psychiatric hospital in Mashhad from the beginning of 2007 until the end of 2009 were used. These patients were followed up until the end of 2018 for readmission. The Cox model with gamma frailty and Bayesian approach were used to determine the effective factors of frequent recurrences.

History of head trauma, substance abuse, and legal conflict had a positive impact on recurrences, while age had a negative effect on recurrences and the risk of recurrence was higher in younger people (P < 0.05). The variance estimation of frailty effect was 0.97 that indicates a correlation between the recurrence intervals of bipolar I patients, owing to a heterogeneity among patients.

Based on the results, a higher risk of recurrence of bipolar I disorder was found in younger patients and those with a history of head trauma, substance abuse, and legal conflicts. Further investigations are required to account for the genetic factor and psychosocial exposure during critical periods applying this model.

To apply a novel method to adjust for HIV knowledge as an unmeasured confounder for the effect of unsafe injection on future HIV testing.

The data were collected from 601 HIV-negative persons who inject drugs (PWID) from a cohort in San Francisco. The panel-data generalized estimating equations (GEE) technique was used to estimate the adjusted risk ratio (RR) for the effect of unsafe injection on not being tested (NBT) for HIV. Expert opinion quantified the bias parameters to adjust for insufficient knowledge about HIV transmission as an unmeasured confounder using Bayesian bias analysis.

Expert opinion estimated that 2.5%–40.0% of PWID with unsafe injection had insufficient HIV knowledge; whereas 1.0%–20.0% who practiced safe injection had insufficient knowledge. Experts also estimated the RR for the association between insufficient knowledge and NBT for HIV as 1.1-5.0. The RR estimate for the association between unsafe injection and NBT for HIV, adjusted for measured confounders, was 0.96 (95% confidence interval: 0.89,1.03). However, the RR estimate decreased to 0.82 (95% credible interval: 0.64, 0.99) after adjusting for insufficient knowledge as an unmeasured confounder.

Our Bayesian approach that uses expert opinion to adjust for unmeasured confounders revealed that PWID who practice unsafe injection are more likely to be tested for HIV – an association that was not seen by conventional analysis.

Breast milk is an ideal food for the healthy growth and development of infants. Breastfeeding is associated with benefits of lifelong health for both infants and mothers. This study aims to investigate the factors affecting breastfeeding duration in primiparous women referring to Tehran health centers.

In this analytical study, the population consisted of primiparous women of reproductive age who referred to Tehran health centers in 2015-2016 having a child aged 2-5 years. Data were collected by a questionnaire for measuring the level of Health Literacy for Iranian Adults (HELIA) in the urban population, a Socio-Economic Status (SES) questionnaire and interviews with mothers. Statistical analysis was done using Bayesian Poisson regression model and OpenBUGS software.

In the present study, the minimum and maximum of breastfeeding duration were one and 24 months respectively, and the median duration of breastfeeding was 20 months. Also, exclusive breastfeeding was reported at 50.5%. The variables age of mother (CI 95%: -0.01, -0.008), health literacy score (CI 95%: 0.01, 0.02) and the first-time breastfeeding more than one hour after birth (CI 95%: -0.34, -0.04) had significant relationship with breastfeeding duration.

The health literacy score, the age of mother and the first-time breastfeeding more than one hour after birth had a significant relationship with breastfeeding duration. Therefore, considering the importance of the effect of maternal health literacy on breastfeeding, it is suggested that mothers of prepregnancy have the ability to obtain a high score of health literacy