An Exploration of COVID-19 Pandemic and its Consequences on FMCG Industry in Bangladesh

2020 ◽  
Vol 7 (3) ◽  
pp. 145-155
Author(s):  
Mohammad Imtiaz Hossain ◽  
Mohammad Rashed Hasan Polas ◽  
Md. Mizanur Rahman ◽  
Tahiya Islam ◽  
Yasmin Jamadar

The main objective of the article was to explore the impact and consequences of Novel Coronavirus (2019-nCoV) on the FMCG Industry in Bangladesh. To achieve the research objective Qualitative methodology was applied by using focus group discussion on the online platforms during the movement restriction period. We collected data from four informants and they were chosen based on their professional relevancy with the FMCG industry. Existing documents also analyzed. This study found that COVID-19 has significant negative impacts on the fast-moving consumer goods (FMCG) industry. The informants provide the miserable scenario of the industry during this pandemic besides suggesting possible corporate strategies. This article discusses the impacts of COVID-19 in Bangladesh, in order to provide a better understanding to government and practitioners of why improving the management of response to infectious disease outbreaks is so critical for a country’s economy, its society, and its place in the global community. 

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Cencetti ◽  
G. Santin ◽  
A. Longa ◽  
E. Pigani ◽  
A. Barrat ◽  
...  

AbstractDigital contact tracing is a relevant tool to control infectious disease outbreaks, including the COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features and heterogeneities of real-world contact patterns influencing contagion dynamics. We fill this gap with a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread in real environments. We find that restrictive policies are more effective in containing the epidemic but come at the cost of unnecessary large-scale quarantines. Policy evaluation through their efficiency and cost results in optimized solutions which only consider contacts longer than 15–20 minutes and closer than 2–3 meters to be at risk. Our results show that isolation and tracing can help control re-emerging outbreaks when some conditions are met: (i) a reduction of the reproductive number through masks and physical distance; (ii) a low-delay isolation of infected individuals; (iii) a high compliance. Finally, we observe the inefficacy of a less privacy-preserving tracing involving second order contacts. Our results may inform digital contact tracing efforts currently being implemented across several countries worldwide.


2021 ◽  
Vol 11 (11) ◽  
pp. 5114
Author(s):  
Hyung-Chul Rah ◽  
Hyeon-Woong Kim ◽  
Aziz Nasridinov ◽  
Wan-Sup Cho ◽  
Seo-Hwa Choi ◽  
...  

In this paper we demonstrate the threshold effects of infectious diseases on livestock prices. Daily retail prices of pork and chicken were used as structured data; news and SNS mentions of African Swine Fever (ASF) and Avian Influenza (AI) were used as unstructured data. Models were tested for the threshold effects of disease-related news and SNS frequencies, specifically those related to ASF and AI, on the retail prices of pork and chicken, respectively. The effects were found to exist, and the values of ASF-related news on pork prices were estimated to be −9 and 8, indicating that the threshold autoregressive (TAR) model can be divided into three regimes. The coefficients of the ASF-related SNS frequencies on pork prices were 1.1666, 0.2663 and −0.1035 for regimes 1, 2 and 3, respectively, suggesting that pork prices increased by 1.1666 Korean won in regime 1 when ASF-related SNS frequencies increased. To promote pork consumption by SNS posts, the required SNS frequencies were estimated to have impacts as great as one standard deviation in the pork price. These values were 247.057, 1309.158 and 2817.266 for regimes 1, 2 and 3, respectively. The impact response periods for pork prices were estimated to last 48, 6, and 8 days for regimes 1, 2 and 3, respectively. When the prediction accuracies of the TAR and autoregressive (AR) models with regard to pork prices were compared for the root mean square error, the prediction accuracy of the TAR model was found to be slightly better than that of the AR. When the threshold effect of AI-related news on chicken prices was tested, a linear relationship appeared without a threshold effect. These findings suggest that when infectious diseases such as ASF occur for the first time, the impact on livestock prices is significant, as indicated by the threshold effect and the long impact response period. Our findings also suggest that the impact on livestock prices is not remarkable when infectious diseases occur multiple times, as in the case of AI. To date, this study is the first to suggest the use of SNS to promote meat consumption.


2021 ◽  
Author(s):  
satya katragadda ◽  
ravi teja bhupatiraju ◽  
vijay raghavan ◽  
ziad ashkar ◽  
raju gottumukkala

Abstract Background: Travel patterns of humans play a major part in the spread of infectious diseases. This was evident in the geographical spread of COVID-19 in the United States. However, the impact of this mobility and the transmission of the virus due to local travel, compared to the population traveling across state boundaries, is unknown. This study evaluates the impact of local vs. visitor mobility in understanding the growth in the number of cases for infectious disease outbreaks. Methods: We use two different mobility metrics, namely the local risk and visitor risk extracted from trip data generated from anonymized mobile phone data across all 50 states in the United States. We analyzed the impact of just using local trips on infection spread and infection risk potential generated from visitors' trips from various other states. We used the Diebold-Mariano test to compare across three machine learning models. Finally, we compared the performance of models, including visitor mobility for all the three waves in the United States and across all 50 states. Results: We observe that visitor mobility impacts case growth and that including visitor mobility in forecasting the number of COVID-19 cases improves prediction accuracy by 34. We found the statistical significance with respect to the performance improvement resulting from including visitor mobility using the Diebold-Mariano test. We also observe that the significance was much higher during the first peak March to June 2020. Conclusion: With presence of cases everywhere (i.e. local and visitor), visitor mobility (even within the country) is shown to have significant impact on growth in number of cases. While it is not possible to account for other factors such as the impact of interventions, and differences in local mobility and visitor mobility, we find that these observations can be used to plan for both reopening and limiting visitors from regions where there are high number of cases.


2020 ◽  
Author(s):  
Fidisoa Rasambainarivo ◽  
Anjarasoa Rasoanomenjanahary ◽  
Joelinotahiana Hasina Rabarison ◽  
Tanjona Ramiadantsoa ◽  
Rila Ratovoson ◽  
...  

AbstractQuantitative estimates of the impact of infectious disease outbreaks are required to develop measured policy responses. In many low- and middle-income countries, inadequate surveillance and incompleteness of death registration are important barriers. Here, we characterize how large an impact on mortality would have to be to be detectable using the uniquely detailed mortality notification data from the city of Antananarivo in Madagascar, with application to a recent measles outbreak. The weekly mortality rate of children during the 2018-2019 measles outbreak was 154% above the expected value at its peak, and the signal can be detected earlier in children than in the general population. This approach to detecting anomalies from expected baseline mortality allows us to delineate the prevalence of COVID-19 at which excess mortality would be detectable with the existing death notification system in the capital of Madagascar. Given current age-specific estimates of the COVID-19 fatality ratio and the age structure of the population in Antananarivo, we estimate that as few as 11 deaths per week in the 60-70 years age group (corresponding to an infection rate of approximately 1%) would detectably exceed the baseline. Data from 2020 will undergo necessary processing and quality control in the coming months. Our results provide a baseline for interpreting this information.


2021 ◽  
Author(s):  
Ann Liljas ◽  
Lenke Morath ◽  
Bo Burström ◽  
Pär Schön ◽  
Janne Agerholm

Abstract Background: Infectious disease outbreaks are common in care homes, often with substantial impact on the rates of infection and mortality of the residents, who primarily are older people vulnerable to infections. There is growing evidence that organisational characteristics of staff and facility might play a role in infection outbreaks however such evidence have not previously been systematically reviewed. Therefore, this systematic review aims to examine the impact of facility and staff characteristics on the risk of infectious disease outbreaks in care homes.Methods: Five databases were searched. Studies considered for inclusion were of any design reporting on an outbreak of any infectious disease in one or more care homes providing care for primarily older people with original data on: facility size, facility location (urban/rural), facility design, use of temporary hired staff, staff compartmentalizing, residence of staff, and/or nursing aides hours per resident. Retrieved studies were screened, assessed for quality, and analysed employing a narrative synthesis.Results: Sixteen studies (8 cohort studies, 6 cross-sectional studies, 2 case-control) were included from the search which generated 10,424 unique records. COVID-19 was the most commonly reported cause of outbreak (n=11). The other studies focused on influenza, respiratory and gastrointestinal outbreaks. Most studies reported on the impact of facility size (n=11) followed by facility design (n=4), use of temporary hired staff (n=3), facility location (n=2), staff compartmentalizing (n=2), nurse aides hours (n=2) and residence of staff (n=1). Findings suggest that urban location and larger facility size may be associated with greater risks of an infectious outbreak. Additionally, the risk of a larger outbreak seems lower in larger facilities. Whilst staff compartmentalizing may be associated with lower risk of an outbreak, staff residing in highly infected areas may be associated with greater risk of outbreak. The influence of facility design, use of temporary staff, and nurse aides hours remains unclear.Conclusions: This systematic review suggests that larger facilities have greater risks of infectious outbreaks, yet the risk of a larger outbreak seems lower in larger facilities. Due to lack of robust findings the impact of facility and staff characteristics on infectious outbreaks remain largely unknown.PROSPERO: CRD42020213585


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arvind Chhabra ◽  
Mehak Munjal ◽  
Prabhu Chandra Mishra ◽  
Kritika Singh ◽  
Debjanee Das ◽  
...  

PurposeThe novel coronavirus has not only caused significant illness and loss of life, it has caused major disruption at local, national and global levels. While the healthcare industry is experiencing growth during the pandemic, disruption to travel has affected medical tourism. This article considers the short-term factors affecting medical tourism and how they could be mitigated by incorporating technological advances to secure long-term growth.Design/methodology/approachThe study examines data provided by the Indian government as well as from non-government sources available in the public domain to review the impact of coronavirus disease 2019 (COVID-19) on medical tourism. The authors also examine data on technological advances in the healthcare industry that could help to reduce the impact of the pandemic.FindingsThis study’s findings show that while in-person services have been seriously impacted in the short term, technological adaptation of medical services to facilitate remote medical consultation has significantly increased. This has enlarged the business opportunities available to hospitals and general practitioners, and it could be leveraged to enhance medical tourism.Originality/valueThe article provides an analysis of the impact of the pandemic on medical tourism and how technology could be used to overcome short-term negative impacts and support longer-term development.


2021 ◽  
Author(s):  
Tianna Loose ◽  
Alejandro Vásquez-Echeverría

The novel coronavirus has taken a catastrophic toll worldwide on physical and mental health. We focused on the psychosocial impact among students in Uruguay, a country relatively protected from the pandemic. Our study had three main aims : 1) describe in detail the impact among university students, 2) identify relationships between different dimensions and 3) highlight the factors determinant of mental distress. We designed a multi-dimensional questionnaire to investigate the perceived impact on the lives of students. The questionnaire was administered to 144 undergraduates in Uruguay online while the university was closed. 38-66% of students indicated increases in signs of anxiety, depression or sleep disturbances. Independently of other related factors, increases in substance use, impairments in social relationships, negative impacts of school closures, and personal economic worries explained 41% of variance in psychological distress. Findings are discussed in terms of policies for public health and future directions for research on mental health.


2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Doret de Rooij ◽  
Evelien Belfroid ◽  
Renske Eilers ◽  
Dorothee Roßkamp ◽  
Corien Swaan ◽  
...  

Background. As demonstrated during the global Ebola crisis of 2014–2016, healthcare institutions in high resource settings need support concerning preparedness during threats of infectious disease outbreaks. This study aimed to exploratively develop a standardized preparedness system to use during unfolding threats of severe infectious diseases. Methods. A qualitative three-step study among infectious disease prevention and control experts was performed. First, interviews (n=5) were conducted to identify which factors trigger preparedness activities during an unfolding threat. Second, these triggers informed the design of a phased preparedness system which was tested in a focus group discussion (n=11). Here preparedness activities per phase and per healthcare institution were identified. Third, the preparedness system was completed and verified in individual interviews (n=3). Interviews and the focus group were recorded, transcribed, and coded for emerging themes by two researchers independently. Data were analyzed using content analysis. Results. Four preparedness phases were identified: preparedness phase green is a situation without the presence of the infectious disease threat that requires centralized care, anywhere in the world. Phase yellow is an outbreak in the world with some likelihood of imported cases. Phase orange is a realistic chance of an unexpected case within the country, or unrest developing among population or staff; phase red is cases admitted to hospitals in the country, potentially causing a shortage of resources. Specific preparedness activities included infection prevention, diagnostics, patient care, staff, and communication. Consensus was reached on the need for the development of a preparedness system and national coordination during threats. Conclusions. In this study, we developed a standardized system to support institutional preparedness during an increasing threat. Use of this system by both curative healthcare institutions and the (municipal) public health service, could help to effectively communicate and align preparedness activities during future threats of severe infectious diseases.


2020 ◽  
Vol 50 (15) ◽  
pp. 2498-2513
Author(s):  
Jing-Li Yue ◽  
Wei Yan ◽  
Yan-Kun Sun ◽  
Kai Yuan ◽  
Si-Zhen Su ◽  
...  

AbstractThe upsurge in the number of people affected by the COVID-19 is likely to lead to increased rates of emotional trauma and mental illnesses. This article systematically reviewed the available data on the benefits of interventions to reduce adverse mental health sequelae of infectious disease outbreaks, and to offer guidance for mental health service responses to infectious disease pandemic. PubMed, Web of Science, Embase, PsycINFO, WHO Global Research Database on infectious disease, and the preprint server medRxiv were searched. Of 4278 reports identified, 32 were included in this review. Most articles of psychological interventions were implemented to address the impact of COVID-19 pandemic, followed by Ebola, SARS, and MERS for multiple vulnerable populations. Increasing mental health literacy of the public is vital to prevent the mental health crisis under the COVID-19 pandemic. Group-based cognitive behavioral therapy, psychological first aid, community-based psychosocial arts program, and other culturally adapted interventions were reported as being effective against the mental health impacts of COVID-19, Ebola, and SARS. Culturally-adapted, cost-effective, and accessible strategies integrated into the public health emergency response and established medical systems at the local and national levels are likely to be an effective option to enhance mental health response capacity for the current and for future infectious disease outbreaks. Tele-mental healthcare services were key central components of stepped care for both infectious disease outbreak management and routine support; however, the usefulness and limitations of remote health delivery should also be recognized.


2020 ◽  
pp. jech-2020-214051 ◽  
Author(s):  
Matt J Keeling ◽  
T Deirdre Hollingsworth ◽  
Jonathan M Read

ObjectiveContact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Importation of novel coronavirus (COVID-19) from China and elsewhere into the UK highlights the need to understand the impact of contact tracing as a control measure.DesignDetailed survey information on social encounters from over 5800 respondents is coupled to predictive models of contact tracing and control. This is used to investigate the likely efficacy of contact tracing and the distribution of secondary cases that may go untraced.ResultsTaking recent estimates for COVID-19 transmission we predict that under effective contact tracing less than 1 in 6 cases will generate any subsequent untraced infections, although this comes at a high logistical burden with an average of 36 individuals traced per case. Changes to the definition of a close contact can reduce this burden, but with increased risk of untraced cases; we find that tracing using a contact definition requiring more than 4 hours of contact is unlikely to control spread.ConclusionsThe current contact tracing strategy within the UK is likely to identify a sufficient proportion of infected individuals such that subsequent spread could be prevented, although the ultimate success will depend on the rapid detection of cases and isolation of contacts. Given the burden of tracing a large number of contacts to find new cases, there is the potential the system could be overwhelmed if imports of infection occur at a rapid rate.


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