Spatiotemporal Study of COVID-19 in Fars Province, Iran, October-November 2020: Establishment of Early Warning System.

Background: Using time series and spatiotemporal analyses, this study aimed to establish an Early Warning System (EWS) for COVID-19 in Fars province Iran. Methods: A EWS was conducted on (i) daily basis city-level time series data including 53 554 cases recorded during 18 February-30 September 2020, which were applied to forecast COVID-19 cases during 1 October-14 November 2020, and (ii) the spatiotemporal analysis, which was conducted on the forecasted cases to predict spatiotemporal outbreaks of COVID-19. Results: A total of 55 369 cases were forecasted during 1 October-14 November 2020, most of which (26.9%) occurred in Shiraz. In addition, 65.80% and 34.20% of the cases occurred in October and November, respectively. Four significant spatiotemporal outbreaks were predicted, with the Most Likely Cluster (MLC) occurring in ten cities during 2-22 October (P < 0.001 for all). Moreover, subgroup analysis demonstrated that Zarrindasht was the canon of the epidemic on 6 October (P=0.04). As a part of EWS, the epidemic was triggered from Jahrom, involving the MLC districts in the center, west, and south parts of the province. Then, it showed a tendency to move towards Zarrindasht in the south and progress to Lar in the southernmost part. Afterwards, it simultaneously progressed to Fasa and Sepidan in the central and northwestern parts of the province, respectively. Conclusion: EWS, which was established based on the current protocol, alarmed policymakers and health managers on the progression of the epidemic and on where and when to implement medical facilities. These findings can be used to tailor province-level policies to servile the ongoing epidemic in the area; however, governmental level effort is needed to control the epidemic at a larger scale in the future.

Efficacy of single-dose and double-dose ivermectin early treatment in preventing progression to hospitalization in mild COVID-19: A multi-arm, parallel-group randomized, double-blind, placebo-controlled trial.

BACKGROUND AND OBJECTIVE: Ivermectin is a known anti-parasitic agent that has been investigated as an antiviral agent against coronavirus disease 2019 (COVID-19). This study aimed to evaluate the efficacy of ivermectin in mild COVID-19 patients. METHODS: In this multi-arm randomized clinical trial conducted between 9 April 2021 and 20 May 2021, a total of 393 patients with reverse transcription-PCR-confirmed COVID-19 infection and mild symptoms were enrolled. Subjects were randomized in a 1:1:1 ratio to receive single-dose ivermectin (12 mg), double-dose ivermectin (24 mg) or placebo. The primary outcome was need for hospitalization. RESULTS: There was no significant difference in the proportion of subjects who required hospitalization between the placebo and single-dose ivermectin groups (absolute difference in the proportions: -2.3 [95% CI = -8.5, 4.1]) and between the placebo and double-dose ivermectin groups (absolute difference in the proportions: -3.9 [95% CI = -9.8, 2.2]). The odds of differences in mean change in severity score between single-dose ivermectin and placebo groups (ORdifference  = 1.005 [95% CI: 0.972, 1.040]; p = 0.762) and double-dose ivermectin and placebo groups (ORdifference  = 1.010 [95% CI: 0.974, 1.046]; p = 0.598) were not statistically significant. None of the six adverse events (including mild dermatitis, tachycardia and hypertension) were serious and required extra action. CONCLUSION: Single-dose and double-dose ivermectin early treatment were not superior to the placebo in preventing progression to hospitalization and improving clinical course in mild COVID-19.

Epidemiological Study of Infection and Death Due to COVID-19 in Fars Province, Iran, From February to September 2020.

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has entered our lives with the fear of outbreak, death, and recurrence. Our objective in this study is to evaluate the epidemiological features of Coronavirus Disease 2019 (COVID-19) infection and death in Fars province, Iran. Methods: A cross-sectional study was conducted from February 18th to September 30th, 2020, where age, history of underlying diseases, sex, community-wide quarantine, nationality, close contact, pregnancy, medical staff job, traveling , and residency were compared between alive and deceased groups. Data were analyzed using IBM SPSS software, version 22.0, and the significance level was set at 0.05. Results: Regarding 57958 new cases of COVID-19, the basic reproduction number (R0) was estimated as 2.8, requiring a minimum of 65% immunization to reach herd immunity. Moreover, an R0=0.36 was required to reach the endemic state in the region. The incidence, mortality, fatality, and recurrence rates of COVID-19 were estimated as 1347.9 per 100,000 dwellers, 209.5 per 1000,000 dwellers, 1.6 %, and 3.1 per 100,000 dwellers, respectively. Age, history of underlying diseases, urban residency, and the male sex were significantly higher in the deceased group (OR=1.09, 5.48, 1.24, and 1.32; All Ps<0.001, <0.001, 0.005, and <0.001, respectively). In addition, the recurrence rate among positive cases was estimated as 0.23% with a median±inter-quartile range equal to 84±46.25 days. Community-wide quarantine was shown to be a protective factor for death due to COVID-19 (OR=0.58, P=0.005). Conclusion: Community-wide quarantine blocks the transmission of COVID-19 effectively. COVID-19 enjoys no solid immunity. History of underlying diseases, the male sex, urban residency, and age were among the most significant causes of death due to COVID-19. Further investigations are recommended on the genetic structure of SARS-CoV-2, treatments, and vaccination.

Spatial epidemiology and meteorological risk factors of COVID-19 in Fars Province, Iran.

This study aimed at detecting space-time clusters of COVID-19 cases in Fars Province, Iran and at investigating their potential association with meteorological factors, such as temperature, precipitation and wind velocity. Time-series data including 53,554 infected people recorded in 26 cities from 18 February to 30 September 2020 together with 5876 meteorological records were subjected to the analysis. Applying a significance level of P<0.05, the analysis of space-time distribution of COVID-19 resulted in nine significant outbreaks within the study period. The most likely cluster occurred from 27 March to 13 July 2020 and contained 11% of the total cases with eight additional, secondary clusters. We found that the COVID-19 incidence rate was affected by high temperature (OR=1.64; 95% CI: 1.44-1.87), while precipitation and wind velocity had less effect (OR=0.84; 95% CI: 0.75-0.89 and OR=0.27; 95% CI: 0.14-0.51), respectively.