Investigation of an Acute Gastrointestinal Illness Outbreak Linked to Drinking Water in a Higher Educational Institute in East Sikkim, India.

Introduction An acute gastrointestinal illness outbreak was reported in a higher educational institution among students and faculties in East Sikkim, India, from January to February 2023. The investigation was conducted to identify the source of the infection and causative pathogens and prevent the spread of the outbreak. Methods We defined a case as three or more loose stools in 24 hours, abdominal pain, or vomiting with the onset of symptoms between January 16 and February 16, 2023.

Development and validation of a novel scale for antiretroviral therapy readiness among pregnant women in urban Zambia with newly diagnosed HIV infection.

Background: Women who are newly diagnosed with HIV infection during pregnancy may not be ready to immediately initiate lifelong antiretroviral therapy (ART; called Option B +) as is recommended. Lack of "readiness" drives early disengagement from care and undermines prevention of HIV transmission to infants. Several studies have shown high early attrition of women initiating ART in pregnancy.

Machine Learning Algorithms for understanding the determinants of under-five Mortality.

Background: Under-five mortality is a matter of serious concern for child health as well as the social development of any country. The paper aimed to find the accuracy of machine learning models in predicting under-five mortality and identify the most significant factors associated with under-five mortality.

Method: The data was taken from the National Family Health Survey (NFHS-IV) of Uttar Pradesh.

Performance of Machine Learning Classifiers in Classifying Stunting among Under-Five Children in Zambia.

Stunting is a global public health issue. We sought to train and evaluate machine learning (ML) classification algorithms on the Zambia Demographic Health Survey (ZDHS) dataset to predict stunting among children under the age of five in Zambia. We applied Logistic regression (LR), Random Forest (RF), SV classification (SVC), XG Boost (XgB) and Naïve Bayes (NB) algorithms to predict the probability of stunting among children under five years of age, on the 2018 ZDHS dataset.

Prevalence and Determinants of Adverse Pregnancy Outcomes among Women in India: A Secondary Data Analysis.

Objective: The present study aimed to identify the determinants of adverse pregnancy outcomes (abortion, miscarriage, and stillbirth) among women aged 15-49 years in India.

Methodology: Data for the analysis were taken from the latest survey of the National Family Health Survey 2015-2016. The determinants associated with abortion, miscarriage, and stillbirth among women in the age group of 15-49 years were identified.

Parametric survival analysis using R: Illustration with lung cancer data.

Background: Cox regression is the most widely used survival model in oncology. Parametric survival models are an alternative of Cox regression model. In this study, we have illustrated the application of semiparametric model and various parametric (Weibull, exponential, log-normal, and log-logistic) models in lung cancer data by using R software.