Milk-borne diseases through the lens of one health

Reviewing “zoonotic diseases” classically brings to mind human infections contracted in close association with animals, where outdoor occupations and afforested lands usually play a key role in the epidemiological triad. However, there is a very common, yet overlooked route of infection where humans may not come in direct contact with animals or implicated environments. Milk-borne diseases are a unique set of infections affecting all age groups and occupational categories of humans, causing 4% of all the foodborne diseases in the world. The infection reservoir may lie with milch animals and associated enzootic cycles, and the infectious agent is freely secreted into the animal’s milk. Commercial pooling and processing of milk create unique environmental challenges, where lapses in quality control could introduce infective agents during downstream processing and distribution. The infectious agent is finally brought to the doorstep of both rural and urban households through such animal products. The domestic hygiene of the household finally determines human infections. One health approach can target preventive measures like immunization in animals, pasteurization and stringent quality control during the commercial processing of milk, and finally, hygienic practices at the level of the consumer, to reduce the burden of milk-borne diseases. This review hopes to draw the attention of policymakers to this unique route of infection, because it can be easily regulated with cost-effective interventions, to ensure the safety of this precious food product, permeating the life and livelihood of humans from all walks of life

Emerging and re-emerging viral infections in India

The number of outbreaks have  progressively increased since many years in India. In this era of globalization and rapid international travel, any infectious disease in one country can become a potential threat to the entire globe. Outbreaks of Nipah, Zika, Crimean- Congo Haemorrhagic Fever and Kyasanur Forest Disease and have been reported since a decade and now we are facing COVID 19 pandemic. One of the challenges in the prevention of these outbreaks is that as the cases decrease, the felt need declines, the public demand decreases and the mitigation responses get overshadowed by the need of emergency responses elsewhere. The One Health approach is a movement to promote alliance between medicine field, veterinary medicine and environmental sciences to upgrade the health of humans, animals, and ecosystem. The data in this article is compiled from different websites and publications of World Health Organization (WHO), Centre for Disease Control and Prevention (CDC), Integrated Disease Surveillance Programme (IDSP), grey literature and media. There is an urgent need for better surveillance and disease burden assessments in the country and to gain detailed insights into vector biology, factors of environment influencing the diseases, mapping of endemic areas, strengthen intersectoral coordination, infection control practices, and ensure use of Personal Protective Equipment’s (PPE) and availability of drugs and vaccines to handle the outbreaks in a better way

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

An exploratory study on the development of a ‘foodie’ scale: evidence from a study on students in India

Most of us can identify a few foodies from our social network. This suggests that we have an intuitive understanding of what defines a foodie. However, there is no objective way to assess whether someone is a foodie or not. Here, we developed a questionnaire that measures the construct “foodie”, that has been shown through multiple qualitative studies to exert influence over people’s food choices. We operationalised the construct “foodie” and developed a 24-item questionnaire that is psychometrically sound. The items were tested in three empirical studies (n = 470) and the scale was found to have strong internal consistency. Overall, four factors emerged: strong love for food, perceived knowledge of food, food-seeking behaviour, and knowledge acquisition. Each factor displayed associations with other constructs from the literature, and thus, provided substantial evidence for the validity of the scale. We discuss how our measure of foodie introduces a new perspective around people’s relationship with food, is different from similar constructs such as food involvement, and may have important clinically relevant implications to various aspects of social life such as physical and emotional health, food tourism, and food production

Acceptability of Mental Health Facilities and De-addiction Centers in India

Not much is known about disease prevalence, treatment outcomes, trained manpower, programs, and patients’ awareness of diseases from South Asia, compared with the Western world. While other aspects are improving, the quantitative evaluation of awareness of diseases is lagging. Compared with other diseases, the situation for mental health disorders and addiction is worse. While no single study can fully quantify all aspects of awareness, a good starting point is to understand if increasing the number of mental health facilities is beneficial by understanding people’s perception toward the likelihood of contracting various diseases, their preferred approach to treatment, and their perception of whether there are enough current facilities. We surveyed over 8000 families across several states of India and asked if they would treat a particular problem at home, visit a local healer, seek religious council, or go to a modern hospital for treatment. Our questions also included non-medical options to assess how likely people are to avoid trained medical help. We also asked people about their perceived likelihood of a family member ever suffering from (1) diarrhea, (2) high fever, (3) alcoholism, and (4) schizophrenia and other mental health problems. We reversed the order of diseases in our questions for a fraction of the population to evaluate the effect of order of questioning. Finally, we asked, if people feel they have enough local healers, religious places, general hospitals, de-addiction centers, and mental health facilities. Despite the taboo around mental health, many people claimed that their family members were unlikely to contract mental health or addiction problems, people recognized the severe paucity of mental health facilities and de-addiction centers. This raises hope for improving the mental health situation in India. We also found a significant relation between education levels and choices people make, underscoring the positive role education has in improving mental health