Institutional quarantine was one of the key public health measures used to control the spread of the COVID-19. Institutional quarantine has been associated with several psychosocial and economic risks to affected individuals. However, little is known about the psychosocial and economic risks it poses to affected persons in low-resource countries, since it is a relatively new strategy for controlling disease spread in these settings. This article provides insights into the economic and psychosocial risks encountered by affected persons in a low-resource context. We conducted narrative interviews with 20 adults placed under institutional quarantine to contain the COVID-19 pandemic in Uganda. Institutional quarantine exposed affected persons to an intricate range of economic and psychosocial risks including loss of livelihoods and/or income, financial distress, fear, worry, anger, loneliness and stigma. The experience of specific risks was shaped by an intersection of individual and contextual factors. However, disregard for economic and social issues and shortcomings in the implementation of institutional quarantine contributed profoundly to the occurrence of risks. Integration of measures for identification and continuous management of the broad range of potential risks to individuals and bridging gaps in the implementation of institutional quarantine, may help to minimise associated economic and psychosocial risks.

The COVID-19 pandemic which have affected every part of the world have been deemed a public health concern and classified as a pandemic. The government imposing travel bans and quarantine measures have been found to be effective in preventing and reducing the spread of COVID-19. A reduction in physical activity and increase in the consumption of unhealthy foods have been observed to be some of the major implications of quarantine. Adequate physical activity and increased access to healthy foods would help in improving the psychological wellbeing of individuals thereby preventing the development of cardiovascular diseases.

In response to the COVID-19 pandemic, the Philippines placed the majority of the country under enhanced community quarantine, restricting the movement of most of its 100 million plus population. These aggressive measures were initiated on March 15, 2020 and intensified on March 17. According to official data, the number of confirmed COVID-19 cases has exponentially increased during this period, but it is important to note that the number of patients tested also substantially increased during the same period. It is not conclusive that widespread transmission of COVID-19 only started in March and our analysis suggests that community transmission was happening earlier. In discussing extended quarantine measures, it is important to properly understand the trends and recognize the limitations of the data. The unintended consequences on the population, especially in lower-middle income countries with fragile health systems like the Philippines, must be carefully considered.

Social distancing policies put in place during COVID-19 epidemic in addition to helping to limit the spread of the disease also contributed to improving urban air quality. Here we show a decrease in air pollutant concentration as a consequence of mobility reduction in São Paulo during the containment measure which began on 22^nd March 2020. When comparing to foregoing weeks to equivalent periods of 2019, the concentration of most air pollutants sharply decreased in the first days of mobility restriction, to then increase again after government officials downplayed the threat of the disease. This trend is also followed by a decrease in hospital admissions by SARS-influenza. Therefore, despite the great economic and social unrest caused by the pandemic, this unique situation shows that large-scale mobility reduction policy had a significant impact on air quality, benefiting, directly and indirectly, the public health system.

The objective of this study was to compare the mental well-being of French women who were and were not pregnant during the first COVID-19 pandemic lockdown. We performed a nationwide online quantitative survey including all women between 18 and 45 years of age during the second and third weeks of global lockdown (March 25–April 07, 2020). The main outcome measures was the mental well-being measured by the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). This study analysed 275 responses from pregnant women and compared them with those from a propensity score–matched sample of 825 non-pregnant women. The median WEMWBS score was 49.0 and did not differ by pregnancy status. Women living in urban areas reported better well-being, while those with sleep disorders or who spent more than an hour a day watching the news reported poorer well-being. During the first lockdown in France, women had relatively low mental well-being scores, with no significant difference between pregnant and non-pregnant women. More than ever, health-care workers need to find a way to maintain their support for women’s well-being. Minor daily annoyances of pregnancy, such as insomnia, should not be trivialised because they are a potential sign of poor well-being.

The emergence of the COVID-19 outbreak has caused a pandemic situation in over 210 countries. Controlling the spread of this disease has proven difficult despite several resources employed. Millions of hospitalization and deaths have been observed, and thousands of cases daily with many measures in place. Due to the complex nature of COVID-19, we proposed a system of time-fractional equations to understand the transmission of the disease better. Nonlocality involved in the model has made fractional differential equations appropriate for modeling the behavior. However, solving these types of models is computationally demanding. Our proposed generalized compartmental COVID-19 model incorporates effective contact rate, transition rate (from exposed quarantine and recovered to susceptible and infected quarantined individuals), quarantine rate, disease-induced death rate, natural death rate, natural recovery rate, recovery rate of quarantine infected for a holistic study of the coronavirus disease. A detailed analysis of the proposed model is carried out, including the existence and uniqueness of solutions, local and global stability analysis of the disease-free equilibrium analysis, and sensitivity analysis. Furthermore, numerical solutions of the proposed model are obtained with the generalized Adam-Bashforth-Moulton method developed for the fractional order model. Our analysis and solutions profile show that each of these incorporated parameters is very important in controlling the spread of COVID-19, especially quarantining exposed and infected individuals and the effective contact rate. Based on the results with different fractional order, we observe that there seems to be a third or even fourth wave of the spike in cases of COVID-19, which is what is happening right now in many countries.

Objective: The study aimed to characterize the changing landscape of circulating SARS-CoV-2 lineages in the local community of Hong Kong throughout 2022. We examined how adjustments to quarantine arrangements influenced the transmission pattern of Omicron variants in a city with relatively rigorous social distancing measures at that time. Methods: In 2022, a total of 4,684 local SARS-CoV-2 genomes were sequenced using the Oxford Nanopore GridION sequencer. SARS-CoV-2 consensus genomes were generated by MAFFT, and the maximum likelihood phylogeny of these genomes were determined using IQ-TREE. The dynamic changes in lineages were depicted in a time tree created by Nextstrain. Statistical analysis was conducted to assess the correlation between changes in the number of lineages and adjustments to quarantine arrangements. Results: By the end of 2022, a total of 83 SARS-CoV-2 lineages were identified in the community. The increase in the number of new lineages was significantly associated with the relaxation of quarantine arrangements (One-way ANOVA, F(5,47)=18.233, p<0.001)). Over time, Omicron BA.5 sub-lineages replaced BA.2.2 and became the predominant Omicron variants in Hong Kong. The influx of new lineages reshaped the dynamics of Omicron variants in the community without fluctuating the death rate and hospitalization rate (One-way ANOVA, F(5,47)=2.037, p=0.091). Conclusion: The study revealed that even with an extended mandatory quarantine period for incoming travelers, it may not be feasible to completely prevent the introduction and subsequent community spread of highly contagious Omicron variants. Ongoing molecular surveillance of COVID-19 remains essential to monitor the emergence of new recombinant variants.

The bagworms Metisa plana is a recurrent indigenous invasive defoliator in oil palm plantations. A moderate foliar injury can cost up to 40% and above of yield loss for years. As an effective biological control agent (BCA) or by integrated pest management (IPM) on insect pests of economic significance affecting major crops of the countries in Asia-Pacific region, the adoption of the Asian weaver ant Oecophylla smaragdina might support farmers facing outbreaks. Information about the foraging activity and population dynamic (PD) of Oecophylla are important in implementing such program. Oecophylla being an obligate arboreal by nature was observed spending extended periods on the ground by occupying a vast territory under constant surveillance mode, which is significant and valuable feature for pest control. The foraging activity of major workers, their exploratory venture is closely related to systematic predation-hunting activity. The scarcity of population dynamic studies on the Oecophylla species contrast with the reports frequency of subterranean species. Estimation of population density of Oecophylla by direct nest counting method is feasible, practical and sustainable. This is contrasting with calculation done on excavated underground colonies consequential of their extinction. Simulation inaccuracy due to insufficient experimental evidence from using exclusively mathematical models is giving to real time long term field population dynamic more importance. Oecophylla colonies' stability, forager abundance and permanent patrol hunting oriented activity, are key factors for pest reduction. If the evaluation on O. smaragdina is higher, for this last decade, a significant upsurge of study on O. longinoda provided substantial novel highlights. The introduction of Oecophylla may alleviate pests management cost and offers a healthier environment by stopping the harmful usage of broad spectrum contact pesticides.

The sudden onset of the Covid-19 pandemic disrupted the modern multi-national interconnected society and led the countries and societies to enforce unprecedented restrictions on movement. Among myriad containment measures, the policy of trace and quarantine found universal adoption among countries; the swift adoption of the policy was soon met with widespread criticism and opposition activists who questioned the utility and the risk associated with such a large scale collection of data and infringement on the movement of individuals. Consequently, one often tends to be either pro- or anti-trace and quarantine; the ensuing polarizing and politicized left little room for nuance. In this work, we undertake a methodology study to understand the nuances of the impact of different implementations of trace and quarantine. To this end, we design a user-friendly and intuitive tool that can be employed by experts to model the disease dynamics and societal structure. We focus on the study of the cost of policy with respect to quarantine degree, which captures the distance between the person required to quarantine after a person is detected to be infected. Our study results in a surprising conclusion: the cost is not necessarily monotone with respect to the degree of quarantine. Our analysis indicates that governments must curb the urge to adopt simplistic policy and the optimal policy of trace and quarantine for a country strongly depends on its societal structure and disease dynamics.

Mass crises are disruptive to people's mental health. The study aimed to explore mental distress during COVID-19 quarantine in a sample of university workers in Brazil. The survey included sets of questions about demographics, health, and support, an open question about major concerns, and the Clinical Outcome Routine Evaluation (CORE-OM), a measure of mental distress. 407 professionals participated in the study: mean age of 40 years (SD = 11.2), mostly female (67.8%), married (64.8%) and fulfilling social distancing to avoid COVID-19 infection (99%). Using the Consensual Qualitative Research for simple qualitative data (CQR-M) the main areas of concern were grouped into six domains, as follows: Work, Health, Isolation, Personal life and routine, Social environment, and Future. Many responses were multiple. They form categories indicating specific concerns within these domains. Quantitative data were analyzed by identifying the simple effects of potential predictors of mental distress. The results indicated medium effects of help with household chores, psychiatric treatment, age and physical exercise. Having someone available to listen was the only variable with a large effect in reducing mental suffering. The hybrid approach showed that the psychological experience during the pandemic is quite multifaceted and complex pointing new clues for public mental health.

The ongoing outbreak of the novel coronavirus pneumonia (also known as COVID-19) has triggered a series of stringent control measures in China, such as city closure, traffic restrictions, contact tracing and household quarantine. These containment efforts often lead to changes in the contact pattern among individuals of the population. Many existing compartmental epidemic models fail to account for the effects of contact structure. In this paper, we devised a pairwise epidemic model to analyze the COVID-19 outbreak in China based on confirmed cases reported during the period February 3rd--17th, 2020. By explicitly incorporating the effects of family clusters and contact tracing followed by household quarantine and isolation, our model provides a good fit to the trajectory of COVID-19 infections and is useful to predict the epidemic trend. We obtained the average of the reproduction number $R=1.494$ ($95\%$ CI: $1.483-1.507$) for Hubei province and $R=1.178$ ($95\%$ CI: $1.145-1.158$) for China (except Hubei), suggesting that some existing studies may have overestimated the reproduction number by neglecting the dynamical correlations and clustering effects. We forecasted that the COVID-19 epidemic would peak on February 13th ($95\%$ CI: February $9-17$th) in Hubei and 6 days eariler in the regions outside Hubei. Moreover the epidemic was expected to last until the middle of March in China (except Hubei) and late April in Hubei. The sensitivity analysis shows that ongoing exposure for the susceptible and population clustering play an important role in the disease propagation. With the enforcement of household quarantine measures, the reproduction number $R$ effectively reduces and epidemic quantities decrease accordingly. Furthermore, we gave an answer to the public concern on how long the stringent containment strategies should maintain. Through numerical analysis, we suggested that the time for the resumption of work and production in China (except Hubei) and Hubei would be the middle of March and the end of April, 2020, respectively. These constructive suggestions may bring some immeasurable social-economic benefits in the long run.

Background: The cumulative number of patients during the COVID-19 pandemic led to a significant shortage of hospital beds. Many patients may not require hospitalization and can be clinically observed in home settings. However, some psychosocial factors are correlated with unsuccessful home isolation (HI), which might negatively affect the transmission control in the community. Therefore, we developed a new psychosocial screening tool (CCPHIET) for assessing HI suitability and examined its validity and reliability.Methods: This cross-sectional descriptive study included COVID-19 patients who were deemed to be medically safe for 14 days of HI. The CCPHIET is comprised of 8 clinical domains pertinent to HI behavioral compliance and risk. We explored its statistical validity and reliability and discussed the potential utility of this tool. Results: A total of 65 COVID-19 patients participated in this study. Most patients (58.5%) were evaluated as good candidates for HI. The CCPHIET has an acceptable content validity (IOC index > 0.5), moderate internal consistency (Cronbach’s alpha = 0.611) and substantial to excellent inter-rater reliability (Intraclass correlation coefficient = 0.944, Cohen’s kappa= 0.627).Conclusions: To compromise between strict and costly absolute institutional quarantine and the potentially unsuccessful absolute HI, the CCPHIET may help to identify good candidates for HI in mild and asymptomatic COVID-19 patients. This psychosocial information would support the physicians in matching each patient to the most suitable setting. Therefore, safe medical care is provided, unnecessary use of medical resources is spared, and local transmission is contained.

COVID-19 appeared as an infectious disease of global health emergency and the highest public health concern of 21st century for this world due to its high-speed of spread across the globe. The disease started as one single case to a cluster of cases in Wuhan, China (Dec 2019) and within few months with its continuous upsurge of cases spreading globally which has created enormous threat and tension across the global Public health care field. Most significantly to share the fact that, this disease caused high level of Risk Group mortality, high morbidity, health care services burden, panic anxiety, mental trauma and tension, social and economic insecurity, which also collectively surfaced by diverse range of social reaction and political pressure across the world. Also with the appearance of new and unknown pathogenesis of the disease has created the most and significant attention and concern for the scientific community and political leaders as well. The disease also varies much with its pattern of virus, sign, symptoms, characteristics including its epidemiological and public health response (like prevention strategy, diagnoses, case management, treatment pattern) across the countries. However, this variance is comparatively less rather even more in commonality while it comes to basic public health prevention interventions like frequent hand washing, wearing face mask, maintaining social/physical distancing (2 - 6 meter in between), individual isolation and community quarantine for suspected exposure and lockdown in community areas where cases are identified. These are with the most commonly practiced public health interventions to deal with this disease in majority of the epicenters across countries. Also with the progress of the disease with its diverse categorical appearance of sign symptoms which are uniquely portraying this disease is more of a kind of COVID-19 syndrome than as COVID-19. Moreover, various factors including socio economic status, health status, population dynamics, health system and infrastructure, health behavioral pattern, nutrition and food habit and access to information and knowledge made this viral disease one of the historically counted on expensive disease of the modern world to fight for. Specially to mention here, the case fatality rate distinctively vary with the population dynamics and the health system infrastructure and ability factors which have already created clear evidence as explained in this paper how these factors are uniquely distinguished and different from country to country. Apart from the contextual differences, the various kind of ongoing preventive measures (like prevention, diagnosis and treatment) learnt every day from the emerging characteristics and pattern of this viral disease which are most commonly practiced across countries with a variance. According to the Public health prevention practice and interventions, the total world is connected and learning from each other’s public health experiences to fight for the virus. However, the world communities are eagerly waiting to see the result and outcome of the ongoing therapeutics and vaccine trial initiated in several countries, the people of the world are quite optimistic and hopeful that, global scientific community will be able to invent some miraculous and magic solution in upcoming months which ultimately will free the world from this most terrifying COVID-19 pandemic of 21st century.

The present novel corona virus (2019-nCoV) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. The infection induced death rate is also very high. There is no vaccine or anti-viral medicine for such infection. So at this moment a major worldwide problem is that how we can control this pandemic. On the other hand, India is a high population density country, where the corona virus disease (COVID-19) has started to spread from $1^{st}$ week of March, 2020 in a significant number of COVID-19 positive cases. Due to this high population density human to human social contact rate is very high in India. So control of the pandemic COVID-19 in early stage is very urgent and challenging problem. Mathematical models are employed in this paper to study the COVID-19 dynamics, to identify the influential parameters and to find the proper prevention strategies to reduce the outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the key model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impacts on the disease dynamics have also been studied. Future trends of the disease transmission has been Predicted from our model with some control measures. Finally, the positive measures to control the disease have been summarized.

Objective: To use mathematical models to predict the epidemiological impact of lifting the lockdown in London, UK, and alternative strategies to help inform policy in the UK. Methods: A mathematical model for the transmission of SARS-CoV2 in London. The model was parametrised using data on notified cases, deaths, contacts, and mobility to analyse the epidemic in the UK capital. We investigated the impact of multiple non pharmaceutical interventions (NPIs) and combinations of these measures on future incidence of COVID-19. Results: Immediate action at the early stages of an epidemic in the affected districts would have tackled spread. While an extended lockdown is highly effective, other measures such as shielding older populations, universal testing and facemasks can all potentially contribute to a reduction of infections and deaths. However, based on current evidence it seems unlikely they will be as effective as continued lockdown. In order to achieve elimination and lift lockdown within 5 months, the best strategy seems to be a combination of weekly universal testing, contact tracing and use of facemasks, with concurrent lockdown. This approach could potentially reduce deaths by 48% compared with continued lockdown alone. Conclusions: A combination of NPIs such as universal testing, contact tracing and mask use while under lockdown would be associated with least deaths and infections. This approach would require high uptake and sustained local effort but it is potentially feasible as may lead to elimination in a relatively short time scale.

With the outbreak of coronavirus disease 2019 (COVID-19), there is a need for efficient management of patients with mild or no symptoms, which account for the majority. The aim of this study is to introduce the structure and operation protocol of a living and treatment support centre (LTSC) operated by Seoul National University Hospital in South Korea. The existing accommodation facility was converted into a 'patient centre' where patients was isolated. A few Medical staff here performed medical tests and responded to emergencies. Another part of the LTSC was 'remote monitoring centre'. In this center, patients’ self-measured vital signs and symptoms were monitored twice a day, and the medical staff staying here provided video-consultation via a smartphone. During the 3 weeks from March 5 to March 26, 2020, 113 patients were admitted and treated. LTSC could be an efficient alternative to hospital admission in pandemic situation like COVID-19.

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.

We develop a mathematical model to provide epidemic predictions for the 2019-nCov epidemic in Wuhan, China. We use reported case data up to January 31, 2020 from the Chinese Center for Disease Control and Prevention and the Wuhan Municipal Health Commission to parameterize the model. From the parameterized model we identify the number of unreported cases. We then use the model to project the epidemic forward with varying level of public health interventions. The model predictions emphasize the importance of major public health interventions in controlling 2019-nCov epidemics.

Agrilus planipennis is a devastating invasive pest of ash trees. This wood-boring insect native to Asia and established in European Russia about 20 years ago poses a serious threat to ash trees all over Europe. In 2019 we first detected Agrilus planipennis in Ukraine. More than 20 larvae have been collected from under the bark of Fraxinus pennsylvanica trees on 5 September 2019 in Markivka District of Luhansk Region. Coordinates of the localities of collection: 49.614991 N, 39.559743 E; 49.614160 N, 39.572402 E and 49.597043 N, 39.561811 E. The photos of damaged trees with larval galleries, exit holes and larvae are presented. There is no doubt that the pest is established in Ukraine. This fact is important for development of quarantine protocols to prevent or at least slow the further spread of this invasive pest in Europe.

PURPOSE: Our research interrogates Professor Peter Doherty’s warning to Australians in April 2020 that ‘COVID-19 is just as lethal as the Spanish flu’. METHODS: We identified the epicentres of both pandemics, namely metropolitan Sydney in 1919 and metropolitan Melbourne in 2020. Using original sources, we compared the lethality of COVID-19 in these two cities. Lethality was measured by the number and rate of hospitalisations and deaths per 100,000 of population. Using these two measures, we diagnosed the waves of infection, their severity at various points in time and the cumulative impact of the viruses by the end of our in-depth study period, i.e. 30 September in 1919 and 2020. RESULTS: Spanish Flu in 1919 was more than 30 times more lethal than COVID-19 in 2020. The hospital admission and death rates of COVID-19 in Melbourne in 2020 constituted a small fraction of the devastation wrought by the Spanish Flu in Sydney in 1919. The patterns and lethality of the pandemic waves were also strikingly different. DISCUSSION AND CONCLUSION: Both pandemics broke out with the arrival of unknown pathogens against which vaccines and antivirals did not exist. Professor Doherty’s warning was perhaps taken seriously and that partly explains the findings of this study. Containing infection in 1919 and 2020 threw the burden on nonpharmaceutical interventions (NPIs) such as ‘protective sequestration’ (quarantine), contact tracing, lockdowns and masks. We discuss the effectiveness of these. Despite the failures of genomic analysis and the weaknesses of the contact tracing system due to mismanagement, it was persistent and detailed contact tracing that provided the best explanation for why NPIs in 2020 were more effective than in 1919 and therefore contributed to the lower lethality of the COVID-19 pandemic in its first year.

The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures. Among these, mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to limit the spread of the virus. In this article, we aim to evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population through a Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. Excluding the value of monetized health, the Benefit-Cost ratio was estimated at approximately 0.45. However, if monetized health is included in the calculation, the ratio is close to 1.20. The monetization of health is the critical element that tips the scales in favour of the desirability of screening. Screenings with the highest return are those that maximize the percentage of positives detected.

The prolonged lockdown imposed to contain the COVID-19 pandemic prevented many people from direct contact with nature and greenspaces, raising alarms for a possible worsening of mental health. This study investigates the effectiveness of a simple and affordable remedy for improving psychological well-being, based on audio-visual stimuli brought by a short computer video showing forest environments, with an urban video as a control. Randomly selected participants were assigned the forest or urban video, to look at and listen early in the morning, and filled questionnaires. In particular, the State-Trait Anxiety Inventory (STAI) Form Y, collected in baseline condition and at the end of the study, and the Part II of the Sheehan Patient Rated Anxiety Scale (SPRAS), collected every day immediately before and after watching the video. The virtual exposure to forest environments showed effective to reduce perceived anxiety levels in in people forced by lockdown in limited spaces and environmental deprivation. Although significant, the effects were observed only in the short term, highlighting the limitation of the virtual experiences. The reported effects might also represent a benchmark to disentangle the determinants of health effects due to real forest experiences, for example, the inhalation of biogenic volatile organic compounds (BVOC).

Decisions affecting the COVID-19 pandemic, by the individual and those with highest authority, are being made on the basis of unreliable data. Data about cases and deaths are collected daily but represent only a sample of reality. Statistics convert sample data into more reliable estimates. However, statistics have no magical powers; reliability requires dependable data. It is futile to rail against this darkness; COVID-19 is not a scientific experiment. However, we must do better both with data collection and data analysis. In this review, I focus on one element of the data, the asymptomatic case of COVID-19. Without reliable information about this number, decision makers are significantly blinded. By its nature, the asymptomatic case is hidden but contaminating to understanding COVID-19. The true case rate and death rate per case are unknowable without knowing the fraction of cases that are asymptomatic. The best estimate of asymptomatic cases is in the CDC document: COVID-19 Pandemic Planning Scenarios. For four different scenarios the estimates range from 10% to 70%, with the best estimate of 40% for asymptomatic cases. However, even the definition of the asymptomatic case is problematic. In simplest terms, two elements are required: an infection and no symptoms. How is “no symptoms” to be usefully defined? It appears to be analogous to pontificating about black swans from studying only white swans. It implies infection, but how is infection defined? Is it presence of the virus, replication of the virus, or presence of antibodies? Is asymptomatic disease an oxymoron? Without extensive, purposeful screening for specifically defined, essential symptoms and appropriate virus and antibody testing over time, the class of asymptomatic cases remains unknown. Current estimates range from <20% to ˃80%. If low, it can be ignored; if high, it dramatically and proportionately lowers the case rate and the death rate per case. Consequentially, the asymptomatic rate dramatically affects our societal and political responses. In this focused review, we assess the limitations of the published estimates, bring attention to the importance of obtaining accurate data, and exhort that high priority be given in the scientific community to understanding the issue, asymptomatic COVID-19 cases.

COVID-19 has affected 212 countries around the world, killing nearly 300,000 and infecting more than 4.4 million by May 14, 2020. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of communicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses. However, the country has just 127,000 hospital beds, 91,000 of them in government-run hospitals. Researchers say, the country’s economy is economy is losing BDT 33 billion every day from its service and agriculture sectors during the nationwide shutdown.