Title: Seroprevalence of Bluetongue virus originating among camels from southern Punjab, Pakistan
Abstract:
Blood transfusion is generally considered safe after cross-matching the blood but there is risk of transmission of transfusion related infections. Screening for many infectious diseases is done to reduce the risk of transmission of infections to the recipients. However, with screening, an odd of catching hepatitis B and C from donated blood is 1 in 300,000 and 1 in 1.5 million respectively. The aim of the study was to determine sero-prevalence of hepatitis B and C virus in local population of province Punjab, Pakistan. This study was conducted at department for pathology and community medicine, Sahiwal Medical College, Sahiwal, Pakistan from 2012-2017. Blood grouping was done by forward and reverse blood grouping while sera were screened for anti-HCV and HBsAg using rapid diagnostic kits.
Biography:
Dr. Muhammad Hassam Rehm, was born and raised in Pakistan. After completion of MBBS in 2007, he worked in Lahore (Pakistan) as Medical Officer and later on moved to Australia for my Post-graduate studies in Master in Health Management (MHM) from Public Health Department University of New South Wales, Sydney Australia. In 2012, he started his career as a Lecturer in Community Medicine/ Public Health department of Sahiwal Medical College, Sahiwal. Since 2015, He is working as Assistant Professor of Community Medicine/ Public Health Department in the same institute.
Title: Meeting the SDG target: challenges of estimation of causes of death due to NCDs in India
Abstract:
The 2030 Agenda for Sustainable Development recognizes noncommunicable diseases (NCDs) as a major challenge for sustainable development.(1) More than half of all countries are predicted to fail to reach the UN target to reduce premature deaths from cancers, cardiovascular disease, chronic respiratory disease, and diabetes by 2030 (2). The challenge is seen at many levels: detecting, treating and ensuring follow up and keeping disease status under control. In addition, one often neglected aspect is the ascertainment of NCD as a cause of death. This is a crucial element to determine whether a country has achieved SDG Target 3.4 .In developing countries like India, most deaths take place at home without medical attention and a proper certification of the cause of death is often not available. In India, the system of death verification is done through the Sample Registration System (3) whereby a verbal autopsy is conducted in a sample of deaths by trained persons after which a trained physician assigns the cause of death. This system has its advantages and disadvantages. Verbal autopsy takes place approximately six months after death, therefore recall of events leading to death is likely to be compromised. Secondly, NCDs like diabetes, hypertension are usually not the immediate cause of death. They are the underlying conditions which lead to complications and death. However the advantage of the system is that the SRS is a continuous activity which is done by trained persons, and carried out in a representative sample of households, thereby providing a trend of deaths on the community. This system also ensures that all deaths even the ones that take place at home without medical attention are also captured by the system. This paper looks into the challenges of estimating the cause of death in a sample of deaths using verbal autopsy.
Biography:
Baridalyne Nongkynrih, trained in public health and currently working as a faculty in Community Medicine All India Institute of Medical Sciences New Delhi India since 2003. My area of interest is Non Communicable Diseases and health systems. I have worked extensively in the area of primary health care in NCDs with the WHO and Ministry of Health Government of India. Currently since 2017, I am also involved in the sample registration system of India and verbal autopsy based cause of death assignment under the Office of the Registrar General of India where we are developing a system for cause of death estimation for the country.
Title: Social Epidemiology and Health Disparities
Abstract:
Social environments influencing obesity in Israel- A qualitative study among health workers focusing on three ethno-religious groups
The prevalence of overweight or obese is 60% and 30% for adults and children respectively and this burden is higher among the ethnic minorities. Cultural norms and practices are an important aspect of their lives and therefore should be incorporated in epidemiological research. This qualitative study aims to identify the cultural determinants of obesity by studying the social environments among three different ethnic populations in Israel: Ultra-orthodox Jews, Settled Muslim Arabs and the Ethiopian Jews., the latter two being ethnic minorities in the country.
Biography:
Mahasweta Mitra is a skilled public health researcher with seven years of clinical and epidemiological research experience in countries such as India, Israel, and the United States. She currently works at Acumen, LLC, a leading research and consulting firm where she manages several analytical and technical projects in biologics effectiveness and safety surveillance of vaccines, in collaboration with the Food and Drug Administration and other data partners. Her mission is to apply her epidemiological and health policy expertise to generate impact in the evolving global health landscape. Prior to joining Acumen, she was a student at the University of Michigan School of Public Health where she built a strong foundation in mixed-methods methods research in evaluating social determinants of health. She independently led a mixed-methods study assessing the social determinants of health of obesity among adolescents in Israel in collaboration with the Israel Ministry of Health, the qualitative findings of which were presented at the 2018 Michigan Public Health Forum.
Title: Validation of the Population Health Impact Model by using the historical Swedish data on tobacco product use
Abstract:
Philip Morris International has developed the Population Health Impact Model (PHIM) to estimate the reduction in smoking attributable mortality that could result from the marketing of a reduced-risk products (RRPs)* on the population (as a whole) of the market where the RRP is introduced. The PHIM predictions cover mortality from four smoking-related diseases — lung cancer, ischemic heart disease, stroke, and chronic pulmonary obstructive pulmonary disease (COPD). In the absence of long-term epidemiological data, PHIM predictions can only be verified in future studies. An exception is Sweden, where many Swedish smokers have already switched from cigarettes to a proven reduced risk, and non-combustible tobacco product (Swedish snus) for which long-term epidemiologic data is available in the period 1980-2010. Applying the PHIM to the Swedish data, a counterfactual scenario assumes that snus had not been available in Sweden and that the population of Swedish male snus users continued to smoke cigarettes instead. In this case, an increased number of deaths from the four smoking-related diseases has been estimated. Two approaches were used to calculate this counterfactual mortality: 1) indirect standardization considering the mortality rates from other European countries and 2) a “crude method” considering the relative risks of sub-populations with specific smoking and snus use behavior. The distribution of tobacco use habits — snus users (current/former/never) and smokers (current/former/never) — was calculated for 1980-2010 period. Finally, the counterfactual hypothetical mortalities were implemented into the PHIM as input parameters, and the model output was compared with the actual Swedish mortality data in males.
Biography:
Laszlo Pecze has completed his PhD in Epidemiology at the age of 25 from University of Szeged, Hungary. He works as Computational Scientist at Philip Morris International in Neuchatel, Switzerland. He is responsible for computational analysis and statistical programming related to population health impact modelling. He has published five papers in eminent journals in the field of mathematical biology.
Title: Integration of artificial intelligence and nutrigenomics in clinical care has implications for large scale population health
Abstract:
As Big Data becomes available concerning nutrition from studies of nutrigenomics and metabolomics the complexity of programs needed to analyze this information necessitates what is considered AI. In addition to data analysis, AI can assist at the point of care by helping doctors and patients more actively track changes in health status. In both applications, the level of complexity achieved in programming falls under the umbrella of Machine Learning [ML] which is a specific subtype of AI. In this review, we will focus on emerging applications of ML in clinical nutrition and the prospective use of this technology in healthcare management. ML programs are already being widely used in ordinary practice, meanwhile, analysis of nutrigenomics and the interactome is revealing a previously unknown influence of nutrition’s effects. We will discuss the implication of novel insights into nutrition in healthcare and review a few examples of current clinical practices utilizing ML technology. Considering the emerging focus on the relation of genomics in modulating individual nutritional status, we will propose a future research direction to streamline the translation of study data to clinical adjuncts. Detailed reasoning is provided for innovative objectives that support the use of nutritional intervention as a mode of therapy that might impact the progression of many diseases such as neurodegenerative disorders. Overall this represents a paradigm shift in the healthcare system that can have broad global implications.