ABSTRACT
OBJECTIVES: Physical distancing is a control measure against coronavirus disease 2019 (COVID-19). Lockdowns are a strategy to enforce physical distancing in urban areas, but they are drastic measures. Therefore, we assessed the effectiveness of the lockdown measures taken in the world's second-most populous country, India, by exploring their relationship with community mobility patterns and the doubling time of COVID-19. METHODS: We conducted a retrospective analysis based on community mobility patterns, the stringency index of lockdown measures, and the doubling time of COVID-19 cases in India between February 15 and April 26, 2020. Pearson correlation coefficients were calculated between the stringency index, community mobility patterns, and the doubling time of COVID-19 cases. Multiple linear regression was applied to predict the doubling time of COVID-19. RESULTS: Community mobility drastically fell after the lockdown was instituted. The doubling time of COVID-19 cases was negatively correlated with population mobility patterns in outdoor areas (r = -0.45 to -0.58). The stringency index and outdoor mobility patterns were also negatively correlated (r = -0.89 to -0.95). Population mobility patterns (R2 = 0.67) were found to predict the doubling time of COVID-19, and the model's predictive power increased when the stringency index was also added (R2 = 0.73). CONCLUSIONS: Lockdown measures could effectively ensure physical distancing and reduce short-term case spikes in India. Therefore, lockdown measures may be considered for tailored implementation on an intermittent basis, whenever COVID-19 cases are predicted to exceed the health care system's capacity to manage.
ABSTRACT
BACKGROUND & AIM: Probiotics in the gut have been suggested to have a beneficial effect on anxiety response and depressive disorder. Hence we conducted a systematic review and meta-analysis to summarize the effects of probiotics associated with or without pharmacological or psychological therapies in patients with depressive and/or anxiety symptoms or disorders. METHODS: We conducted searches of MEDLINE, EMBASE, CENTRAL, PsycINFO, CINAHL, ProQuest, LILACS, and Web of Science up to February 2020 to identify randomized controlled trials (RCTs) investigating the efficacy of probiotics associated with or without pharmacological or psychological therapies for patient-important outcomes including relief of depressive, anxiety and stress symptoms, cognitive functions, adverse events and quality of life. We used the GRADE approach to rate the overall certainty of the evidence by outcome. The protocol of the systematic review was registered with PROPSERO and published under the number CRD4202016329. RESULTS: 16 RCTs including 1,125 patients proved eligible. Results suggested a significant improvement in using Beck Depression Index (MD, -3.20 [95% CI, -5.91 to -0.49], p = 0.02; I2 = 21%, p = 0.28) for depression symptoms and State-Trait Anxiety Inventory (STAI) (MD, -6.88 [95% CI, -12.35 to -1.41], p = 0.01; I2 = 24%, p = 0.25) for anxiety with overall certainty in evidence rated as moderate and low, respectively. However, Depression Scale (DASS-Depression) (MD, 2.01 [95% CI, -0.80 to 4.82], p = 0.16; I2 = 0%, p = 0.62), Montgomery-Asberg Depression Rating Scale (MADRAS) (MD, -2,41 [95% CI, -10,55 to 5,72], p = 0,56; I2 = 87%, p = 0,006), Anxiety scale (DASS-Anxiety) (MD, 0.49 [95% CI, -4.05 to 5.02], p = 0.83; I2 = 74%, p = 0.05), and Stress Scale (DASS-Stress) (MD, 0.84 [95% CI, -2.64 to 4.33], p = 0.64; I2 = 34%, p = 0.22) showed no significant decrease in the relief of depression, anxiety and stress symptoms of probiotics compared to placebo with overall certainty in evidence rated as very low for all outcomes. We also found no differences in the Beck Anxiety Index (BAI) (MD, -3.21 [95% CI, -6.50 to 0.08], p = 0.06; I2 = 0%, p = 0.88) with overall certainty in evidence rated as low. Results suggested a non-statistically significantly effect of probiotics in the adverse events outcomes. CONCLUSIONS: The current review suggests that probiotics may improve symptoms of depression and anxiety in clinical patients. However, given the limitations in the included studies, RCTs with long-term follow-up and large sample sizes are needed.
Subject(s)
Depression , Probiotics , Anxiety/therapy , Depression/therapy , Humans , India , Randomized Controlled Trials as TopicABSTRACT
Objectives@#Considering the rising menace of coronavirus disease 2019 (COVID-19), it is essential to explore the methods and resources that might predict the case numbers expected and identify the locations of outbreaks. Hence, we have done the following study to explore the potential use of Google Trends (GT) in predicting the COVID-19 outbreak in India. @*Methods@#The Google search terms used for the analysis were “coronavirus”, “COVID”, “COVID 19”, “corona”, and “virus”. GTs for these terms in Google Web, News, and YouTube, and the data on COVID-19 case numbers were obtained. Spearman correlation and lag correlation were used to determine the correlation between COVID-19 cases and the Google search terms. @*Results@#“Coronavirus” and “corona” were the terms most commonly used by Internet surfers in India. Correlation for the GTs of the search terms “coronavirus” and “corona” was high (r > 0.7) with the daily cumulative and new COVID-19 cases for a lag period ranging from 9 to 21 days. The maximum lag period for predicting COVID-19 cases was found to be with the News search for the term “coronavirus”, with 21 days, i.e., the search volume for “coronavirus” peaked 21 days before the peak number of cases reported by the disease surveillance system. @*Conclusions@#Our study revealed that GTs may predict outbreaks of COVID-19, 2 to 3 weeks earlier than the routine disease surveillance, in India. Google search data may be considered as a supplementary tool in COVID-19 monitoring and planning in India.
