Application of Geospatial Technologies in the COVID-19 Fight of Ghana
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ABSTRACT:
SUBMITTER: Sarfo A
PROVIDER: S-EPMC7334632 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
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Project description:Currently, there are no treatment options available for the deadly contagious disease, coronavirus disease 2019 (COVID-19). Drug repurposing is a process of identifying new uses for approved or investigational drugs and it is considered as a very effective strategy for drug discovery as it involves less time and cost to find a therapeutic agent in comparison to the de novo drug discovery process. The present review will focus on the repurposing efficacy of the currently used drugs against COVID-19 and their mechanisms of action, pharmacokinetics, dosing, safety, and their future perspective. Relevant articles with experimental studies conducted in-silico, in-vitro, in-vivo, clinical trials in humans, case reports, and news archives were selected for the review. Number of drugs such as remdesivir, favipiravir, ribavirin, lopinavir, ritonavir, darunavir, arbidol, chloroquine, hydroxychloroquine, tocilizumab and interferons have shown inhibitory effects against the SARS-CoV2 in-vitro as well as in clinical conditions. These drugs either act through virus-related targets such as RNA genome, polypeptide packing and uptake pathways or target host-related pathways involving angiotensin-converting enzyme-2 (ACE2) receptors and inflammatory pathways. Using the basic knowledge of viral pathogenesis and pharmacodynamics of drugs as well as using computational tools, many drugs are currently in pipeline to be repurposed. In the current scenario, repositioning of the drugs could be considered the new avenue for the treatment of COVID-19.
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Project description:The majority of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals remain paucisymptomatic, contrasting with a minority of infected individuals in danger of death. Here, we speculate that the robust disease resistance of most individuals is due to a swift production of type I interferon (IFN?/?), presumably sufficient to lower the viremia. A minority of infected individuals with a preexisting chronic inflammatory state fail to mount this early efficient response, leading to a delayed harmful inflammatory response. To improve the epidemiological scenario, we propose combining: (i) the development of efficient antivirals administered early enough to assist in the production of endogenous IFN?/?; (ii) potentiating early IFN responses; (iii) administering anti-inflammatory treatments when needed, but not too early to interfere with endogenous antiviral responses.
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Project description:The research community is in a race to understand the molecular mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, to repurpose currently available antiviral drugs and to develop new therapies and vaccines against coronavirus disease 2019 (COVID-19). One major challenge in achieving these goals is the paucity of suitable preclinical animal models. Mice constitute ~70% of all the laboratory animal species used in biomedical research. Unfortunately, SARS-CoV-2 infects mice only if they have been genetically modified to express human ACE2. The inherent resistance of wild-type mice to SARS-CoV-2, combined with a wealth of genetic tools that are available only for modifying mice, offers a unique opportunity to create a versatile set of genetically engineered mouse models useful for COVID-19 research. We propose three broad categories of these models and more than two dozen designs that may be useful for SARS-CoV-2 research and for fighting COVID-19.
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Project description:The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. Our focus was driven on tools drawing data from the fields of epidemiology, genomics, interactomics and pharmacology, in order to provide a meaningful depiction of the current state of the art of COVID-19 online resources.
| S-EPMC7665357 | biostudies-literature
Project description:ObjectivesAccording to current reporting, the number of active coronavirus disease 2019 (COVID-19) infections is not evenly distributed, both spatially and temporally. Reported COVID-19 infections may not have properly conveyed the full extent of attention to the pandemic. Furthermore, infection metrics are unlikely to illustrate the full scope of negative consequences of the pandemic and its associated risk to communities.MethodsIn an effort to better understand the impacts of COVID-19, we concurrently assessed the geospatial and longitudinal distributions of Twitter messages about COVID-19 which were posted between March 3rd and April 13th and compared these results with the number of confirmed cases reported for sub-national levels of the United States. Geospatial hot spot analysis was also conducted to detect geographic areas that might be at elevated risk of spread based on both volume of tweets and number of reported cases.ResultsStatistically significant aberrations of high numbers of tweets were detected in approximately one-third of US states, most of which had relatively high proportions of rural inhabitants. Geospatial trends toward becoming hotspots for tweets related to COVID-19 were observed for specific rural states in the United States.DiscussionPopulation-adjusted results indicate that rural areas in the U.S. may not have engaged with the COVID-19 topic until later stages of an outbreak. Future studies should explore how this dynamic can inform future outbreak communication and health promotion.
| S-EPMC7592735 | biostudies-literature
Project description:In late December 2019, a new type of coronavirus was discovered, which was later named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Since its discovery, the virus has spread globally, with 2,975,875 deaths as of 15 April 2021, and has had a huge impact on our health systems and economy. How to suppress the continued spread of new coronary pneumonia is the main task of many scientists and researchers. The introduction of artificial intelligence technology has provided a huge contribution to the suppression of the new coronavirus. This article discusses the main application of artificial intelligence technology in the suppression of coronavirus from three major aspects of identification, prediction, and development through a large amount of literature research, and puts forward the current main challenges and possible development directions. The results show that it is an effective measure to combine artificial intelligence technology with a variety of new technologies to predict and identify COVID-19 patients.
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Project description:The paper investigates the causal relationship between the trust in institutions and compliance with measures introduced to slow down the spread of the novel coronavirus COVID-19 in Slovakia. In addition, the impact of socio-economic characteristics on compliance with introduced measures was analysed. Data were obtained from a survey carried out by the Slovak Academy of Sciences on a representative sample of the Slovak population of 1,000 respondents. To derive the causal relationship between institutional trust and compliance behaviour, a probit regression model was used. Findings suggest that trust in public institutions helps to increase compliance with social distancing. In addition, some socio-economic characteristics such as employment status, age or whether individuals felt endangered by COVID-19 had a positive and statistically significant effect on compliance with measures used to slow the spread of the COVID-19 virus. Institutional trust did not have a statistically significant effect on compliance with face-covering measures. Supplementary Information The online version contains supplementary material available at 10.1007/s11294-021-09818-3.
| S-EPMC8072078 | biostudies-literature
Project description:(1) Background: We collected COVID-19 mortality data and the age distribution of the deceased in France and other European countries, as well as specifically in the cities of Paris and Marseille, and compared them. (2) Methods: Data on mortality related to COVID-19 and the associated age distribution were collected from government institutions in various European countries. In France, data were obtained from INSEE and Santé Publique France. All-cause mortality was also examined in order to study potential excess mortality using EuroMOMO. The Marseille data came from the epidemiological surveillance system. (3) Results: France is one of the European countries most impacted by COVID-19. Its proportion of deaths in people under 60 years of age is higher (6.5%) than that of Italy (4.6%) or Spain (4.7%). Excess mortality (5% more deaths) was also observed. Ile-de-France and the Grand-Est are the two French regions with the highest mortality. The proportion of deaths in the under-60 age group was considerable in Ile-de-France (9.9% vs. 4.5% in the Southern region). There are significantly higher numbers of patients hospitalized, in intensive care and deceased in Paris than in Marseille. (4) Conclusions: No patient management, i.e., from screening to diagnosis, including biological assessment and clinical examination, likely explains the high mortality associated with COVID-19.
| S-EPMC8268313 | biostudies-literature
Project description:The phytotherapeutic properties of Glycyrrhiza glabra (licorice) extract are mainly attributed to glycyrrhizin (GR) and glycyrrhetinic acid (GA). Among their possible pharmacological actions, the ability to act against viruses belonging to different families, including SARS coronavirus, is particularly important. With the COVID-19 emergency and the urgent need for compounds to counteract the pandemic, the antiviral properties of GR and GA, as pure substances or as components of licorice extract, attracted attention in the last year and supported the launch of two clinical trials. In silico docking studies reported that GR and GA may directly interact with the key players in viral internalization and replication such as angiotensin-converting enzyme 2 (ACE2), spike protein, the host transmembrane serine protease 2, and 3-chymotrypsin-like cysteine protease. In vitro data indicated that GR can interfere with virus entry by directly interacting with ACE2 and spike, with a nonspecific effect on cell and viral membranes. Additional anti-inflammatory and antioxidant effects of GR cannot be excluded. These multiple activities of GR and licorice extract are critically re-assessed in this review, and their possible role against the spread of the SARS-CoV-2 and the features of COVID-19 disease is discussed.
| S-EPMC8227143 | biostudies-literature
Project description:BackgroundGhana did not meet the Millennium Development Goal 4 of reducing child mortality by two-thirds and may not meet SDG (2030). There is a need to direct scarce resources to mitigate the impact of the most important risk factors influencing high neonatal deaths. This study applied both spatial and non-spatial regression models to explore the differential impact of environmental, maternal, and child associated risk factors on neonatal deaths in Ghana.MethodsThe study relied on data from the Ghana Demographic and Health Surveys (GDHS) and the Ghana Maternal Health Survey (GMHS) conducted between 1998 and 2017 among 49,908 women of reproductive age and 31,367 children under five (GDHS-1998 = 3298, GDHS-2003 = 3844, GDHS-2008 = 2992, GDHS-2014 = 5884, GMHS-2017 = 15,349). Spatial Autoregressive Models that account for spatial autocorrelation in the data at the cluster-level and non-spatial statistical models with appropriate sampling weight adjustment were used to study factors associated with neonatal deaths, and a p-value less than 0.05 was considered statistically significant.ResultsPopulation density, multiple births, smaller household sizes, high parity, and low birth weight significantly increased the risk of neonatal deaths over the years. Among mothers who had multiple births, the risk of having neonatal deaths was approximately four times as high as the risk of neonatal deaths among mothers who had only single birth [aRR = 3.42, 95% CI: 1.63-7.17, p < 0.05]. Neonates who were perceived by their mothers to be small were at a higher risk of neonatal death compared to very large neonates [aRR = 2.08, 95% CI: 1.19-3.63, p < 0.05]. A unit increase in the number of children born to a woman of reproductive age was associated with a 49% increased risk in neonatal deaths [aRR = 1.49, 95% CI: 1.30-1.69, p < 0.05].ConclusionNeonatal mortality in Ghana remains relatively high, and the factors that predisposed children to neonatal death were birth size that were perceived to be small, low birth weight, higher parity, and multiple births. Improving pregnant women's nutritional patterns and providing special support to women who have multiple deliveries will reduce neonatal mortality in Ghana.
| S-EPMC7953754 | biostudies-literature