Ramadan Fasting Exerts Immunomodulatory Effects: Insights from a Systematic Review

Ramadan is the ninth month of the Islamic lunar calendar and is observed by Muslims as a month of fasting. All Muslim adults are expected to fast; nevertheless certain subgroups, including sick, frail subjects, and pregnant women, among others, are exempted. Ramadan fasting has been shown to impact on body systems in different manners. The influence of Ramadan fasting on immune system regulation remains elusive; however, immune system changes, such as the modulation of body response to various infectious, stressful, and other harmful events, are of great interest during fasting. In this paper, we performed an extensive systematic literature review of different scholarly databases (ISI/Web of Science, Scopus, PubMed,/MEDLINE, Google Scholar, Directory of Open Access Journals, EbscoHOST, Scirus, Science Direct, the Cochrane Library, and ProQuest), using the following key words: “fasting,” “Ramadan,” “Islam,” and “immunity.” Conclusions drawn from these findings included: (1) Ramadan fasting has been shown to only mildly influence the immune system and the alterations induced are transient, returning to basal pre-Ramadan status shortly afterward. (2) Ramadan fasting during the second trimester of pregnancy was shown to be safe and did not result in negative fetal outcomes, or maternal oxidative status alterations. (3) In cardiac patients, Ramadan fasting can have beneficial effects including lipid profile improvement and alleviation of oxidative stress. (4) In asthmatic patients as well as in patients with human immunodeficiency virus/acquired immunodeficiency syndrome and autoimmune disorders, fasting was safe. (5) In psychiatric patients, such as those suffering from schizophrenia, fasting could increase immunologic markers. (6) Fasting Muslim athletes who maintain intensive training schedule during Ramadan showed fluctuations of immunologic markers

Capturing public interest toward new tools for controlling human immunodeficiency virus (HIV) infection exploiting data from Google Trends

Human immunodeficiency virus vaccination and pre-exposure prophylaxis represent two different emerging preventive tools. Google Trends was used to assess the public interest toward these tools in terms of digital activities. Worldwide web searches concerning the human immunodeficiency virus vaccine represented 0.34 percent, 0.03 percent, and 46.97 percent of human immunodeficiency virus, acquired immune deficiency syndrome, and human immunodeficiency virus/acquired immune deficiency syndrome treatment-related Google Trends queries, respectively. Concerning temporal trends, digital activities were shown to increase from 0 percent as of 1 January 2004 percent to 46 percent as of 8 October 2017 with two spikes observed in May and July 2012, coinciding with the US Food and Drug Administration approval. Bursts in search number and volume were recorded as human immunodeficiency virus vaccine trials emerged. This search topic has decreased in the past decade in parallel to the increase in Truvada-related topics. Concentrated searches were noticed among African countries with high human immunodeficiency virus/acquired immune deficiency syndrome prevalence. Stakeholders should take advantage of public interest especially in preventive medicine in high disease burden countries

Correction: Public reaction to Chikungunya outbreaks in Italy-Insights from an extensive novel data streams-based structural equation modeling analysis.

[This corrects the article DOI: 10.1371/journal.pone.0197337.]

Capturing public interest toward new tools for controlling human immunodeficiency virus (HIV) infection exploiting data from Google Trends

Human immunodeficiency virus vaccination and pre-exposure prophylaxis represent two different emerging preventive tools. Google Trends was used to assess the public interest toward these tools in terms of digital activities. Worldwide web searches concerning the human immunodeficiency virus vaccine represented 0.34 percent, 0.03 percent, and 46.97 percent of human immunodeficiency virus, acquired immune deficiency syndrome, and human immunodeficiency virus/acquired immune deficiency syndrome treatment-related Google Trends queries, respectively. Concerning temporal trends, digital activities were shown to increase from 0 percent as of 1 January 2004 percent to 46 percent as of 8 October 2017 with two spikes observed in May and July 2012, coinciding with the US Food and Drug Administration approval. Bursts in search number and volume were recorded as human immunodeficiency virus vaccine trials emerged. This search topic has decreased in the past decade in parallel to the increase in Truvada-related topics. Concentrated searches were noticed among African countries with high human immunodeficiency virus/acquired immune deficiency syndrome prevalence. Stakeholders should take advantage of public interest especially in preventive medicine in high disease burden countries

Correlation between novel data streams traffic and epidemiological cases of Chikungunya virus infection (notified and confirmed).

<p>Correlation between novel data streams traffic and epidemiological cases of Chikungunya virus infection (notified and confirmed).</p

Novel data streams utilized in the current study.

<p>Novel data streams utilized in the current study.</p

Structural equation modeling for notified autochthonous cases of Chikungunya showing the relationships among the novel data streams used in the current study, unadjusted model (3A) and adjusted model (3B) for the internet penetration index.

<p>*statistically significant with p-value less than 0.05; **statistically significant with p-value less than 0.01; ***statistically significant with p-value less than 0.001.</p

Structural equation modeling for notified cases of Chikungunya virus (adjusted model).

<p>Structural equation modeling for notified cases of Chikungunya virus (adjusted model).</p

Structural equation modelling for confirmed, notified and imported cases of Chikungunya virus.

<p>Structural equation modelling for confirmed, notified and imported cases of Chikungunya virus.</p

Structural equation modeling for confirmed cases of Chikungunya virus (adjusted model).

<p>Structural equation modeling for confirmed cases of Chikungunya virus (adjusted model).</p