Insight into vaccination and meteorological factors on daily COVID-19 cases and mortality in Bangladesh.

The ongoing COVID-19 contagious disease caused by SARS-CoV-2 has disrupted global public health, businesses, and economies due to widespread infection, with 676.41 million confirmed cases and 6.77 million deaths in 231 countries as of February 07, 2023. To control the rapid spread of SARS-CoV-2, it is crucial to determine the potential determinants such as meteorological factors and their roles. This study examines how COVID-19 cases and deaths changed over time while assessing meteorological characteristics that could impact these disparities from the onset of the pandemic. We used data spanning two years across all eight administrative divisions, this is the first of its kind--showing a connection between meteorological conditions, vaccination, and COVID-19 incidences in Bangladesh. We further employed several techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Integrated Moving Average with explanatory variables (ARIMAX), and Automatic forecasting time-series model (Prophet). We further analyzed the effects of COVID-19 vaccination on daily cases and deaths. Data on COVID-19 cases collected include eight administrative divisions of Bangladesh spanning March 8, 2020, to January 31, 2023, from available online servers. The meteorological data include rainfall (mm), relative humidity (%), average temperature (°C), surface pressure (kPa), dew point (°C), and maximum wind speed (m/s). The observed wind speed and surface pressure show a significant negative impact on COVID-19 cases (-0.89, 95% confidence interval (CI): 1.62 to -0.21) and (-1.31, 95%CI: 2.32 to -0.29), respectively. Similarly, the observed wind speed and surface pressure show a significant negative impact on COVID-19 deaths (-0.87, 95% CI: 1.54 to -0.21) and (-3.11, 95%CI: 4.44 to -1.25), respectively. The impact of meteorological factors is almost similar when vaccination information is included in the model. However, the impact of vaccination in both cases and deaths model is significantly negative (for cases: 1.19, 95%CI: 2.35 to -0.38 and for deaths: 1.55, 95%CI: 2.88 to -0.43). Accordingly, vaccination effectively reduces the number of new COVID-19 cases and fatalities in Bangladesh. Thus, these results could assist future researchers and policymakers in the assessment of pandemics, by making thorough efforts that account for COVID-19 vaccinations and meteorological conditions.

Correlation of Dengue and Meteorological Factors in Bangladesh: A Public Health Concern.

Dengue virus (DENV) is an enveloped, single-stranded RNA virus, a member of the Flaviviridae family (which causes Dengue fever), and an arthropod-transmitted human viral infection. Bangladesh is well known for having some of Asia's most vulnerable Dengue outbreaks, with climate change, its location, and it's dense population serving as the main contributors. For speculation about DENV outbreak characteristics, it is crucial to determine how meteorological factors correlate with the number of cases. This study used five time series models to observe the trend and forecast Dengue cases. Current data-based research has also applied four statistical models to test the relationship between Dengue-positive cases and meteorological parameters. Datasets were used from NASA for meteorological parameters, and daily DENV cases were obtained from the Directorate General of Health Service (DGHS) open-access websites. During the study period, the mean of DENV cases was 882.26 ± 3993.18, ranging between a minimum of 0 to a maximum of 52,636 daily confirmed cases. The Spearman's rank correlation coefficient between climatic variables and Dengue incidence indicated that no substantial relationship exists between daily Dengue cases and wind speed, temperature, and surface pressure (Spearman's rho; r = -0.007, p > 0.05; r = 0.085, p > 0.05; and r = -0.086, p > 0.05, respectively). Still, a significant relationship exists between daily Dengue cases and dew point, relative humidity, and rainfall (r = 0.158, p < 0.05; r = 0.175, p < 0.05; and r = 0.138, p < 0.05, respectively). Using the ARIMAX and GA models, the relationship for Dengue cases with wind speed is -666.50 [95% CI: -1711.86 to 378.86] and -953.05 [-2403.46 to 497.36], respectively. A similar negative relation between Dengue cases and wind speed was also determined in the GLM model (IRR = 0.98). Dew point and surface pressure also represented a negative correlation in both ARIMAX and GA models, respectively, but the GLM model showed a positive association. Additionally, temperature and relative humidity showed a positive correlation with Dengue cases (105.71 and 57.39, respectively, in the ARIMAX, 633.86, and 200.03 in the GA model). In contrast, both temperature and relative humidity showed negative relation with Dengue cases in the GLM model. In the Poisson regression model, windspeed has a substantial significant negative connection with Dengue cases in all seasons. Temperature and rainfall are significantly and positively associated with Dengue cases in all seasons. The association between meteorological factors and recent outbreak data is the first study where we are aware of the use of maximum time series models in Bangladesh. Taking comprehensive measures against DENV outbreaks in the future can be possible through these findings, which can help fellow researchers and policymakers.

Effects of fine particulate matter (PM2.5) and meteorological factors on the daily confirmed cases of COVID-19 in Bangkok during 2020-2021, Thailand.

The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM2.5) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant (p < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.

Association between Global Monkeypox Cases and Meteorological Factors.

The emergence of an outbreak of Monkeypox disease (MPXD) is caused by a contagious zoonotic Monkeypox virus (MPXV) that has spread globally. Yet, there is no study investigating the effect of climatic changes on MPXV transmission. Thus, studies on the changing epidemiology, evolving nature of the virus, and ecological niche are highly paramount. Determination of the role of potential meteorological drivers including temperature, precipitation, relative humidity, dew point, wind speed, and surface pressure is beneficial to understand the MPXD outbreak. This study examines the changes in MPXV cases over time while assessing the meteorological characteristics that could impact these disparities from the onset of the global outbreak. To conduct this data-based research, several well-accepted statistical techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Automatic forecasting time-series model (Prophet), and Autoregressive Integrated Moving Average with Explanatory Variables (ARIMAX) were applied to delineate the correlation of the meteorological factors on global daily Monkeypox cases. Data on MPXV cases including affected countries spanning from 6 May 2022, to 9 November 2022, from global databases and meteorological data were used to evaluate the developed models. According to the ARIMAX model, the results showed that temperature, relative humidity, and surface pressure have a positive impact [(51.56, 95% confidence interval (CI): -274.55 to 377.68), (17.32, 95% CI: -83.71 to 118.35) and (23.42, 95% CI: -9.90 to 56.75), respectively] on MPXV cases. In addition, dew/frost point, precipitation, and wind speed show a significant negative impact on MPXD cases. The Prophet model showed a significant correlation with rising MPXD cases, although the trend predicts peak values while the overall trend increases. This underscores the importance of immediate and appropriate preventive measures (timely preparedness and proactive control strategies) with utmost priority against MPXD including awareness-raising programs, the discovery, and formulation of effective vaccine candidate(s), prophylaxis and therapeutic regimes, and management strategies.

An opinion on Wastewater-Based Epidemiological Monitoring (WBEM) with Clinical Diagnostic Test (CDT) for detecting high-prevalence areas of community COVID-19 Infections.

Wastewater-Based Epidemiological Monitoring (WBEM) is an efficient surveillance tool during the COVID-19 pandemic as it meets all requirements of a complete monitoring system including early warning, tracking the current trend, prevalence of the disease, detection of genetic diversity as well asthe up-surging SARS-CoV-2 new variants with mutations from the wastewater samples. Subsequently, Clinical Diagnostic Test is widely acknowledged as the global gold standard method for disease monitoring, despite several drawbacks such as high diagnosis cost, reporting bias, and the difficulty of tracking asymptomatic patients (silent spreaders of the COVID-19 infection who manifest nosymptoms of the disease). In this current reviewand opinion-based study, we first propose a combined approach) for detecting COVID-19 infection in communities using wastewater and clinical sample testing, which may be feasible and effective as an emerging public health tool for the long-term nationwide surveillance system. The viral concentrations in wastewater samples can be used as indicatorsto monitor ongoing SARS-CoV-2 trends, predict asymptomatic carriers, and detect COVID-19 hotspot areas, while clinical sampleshelp in detecting mostlysymptomaticindividuals for isolating positive cases in communities and validate WBEM protocol for mass vaccination including booster doses for COVID-19.

Human health risk assessment of PM2.5-bound heavy metal of anthropogenic sources in the Khon Kaen Province of Northeast Thailand.

The study aimed to assess the human health risk of PM2.5-bound heavy metals from anthropogenic sources in Khon Kaen Province, Thailand between December 2020 and February 2021. According to the findings, the geometric mean concentration of PM2.5 in the university area, residential area, industrial zone, and the agricultural zone was 32.78 µg/m3, 50.25 µg/m3, 44.48 µg/m3, and 29.53 µg/m3, respectively. The results showed that the estimated human health risk assessment, in terms of non-carcinogenic risks among children and adults in an urban area (residential and university), industrial zone, and the agricultural area, was of hazard index (HI) value of >1.0 indicating a greater chance of chronic effects occurring. This study showed that exposure to PM2.5-bound heavy metal may increase the likelihood that lasting effects will result in a very high carcinogenic risk (CR) in children in residential areas, and an industrial zone with total carcinogenic risk (TCR) values of 0.23 × 10 1 , and 0.12 × 10 1 , respectively while resulting in a high TCR of 3.34 × 10 - 2 and 4.11 × 10 - 2 within the university areas and agricultural zone, respectively. In addition, health risk assessments among adults demonstrate high TCR values of 4.40 × 10 - 1 (residential area), 2.28 × 10 - 1 (industrial zone), and 7.70 × 10 - 3 (agricultural zone), thus indicating a potential health risk to adults living in these areas while the university area was very low effects on carcinogenic risk ( CR ≤ 10 - 8 ) for adults. Therefore, lowering the risk of exposure to PM2.5 via the respiratory tract, for example, wearing a mask outside is a very effective self-defense strategy for people within and around the study site. This data study strongly supports the implementation of the air pollutant emission source reduction measures control and health surveillance.

A review on microplastics and nanoplastics in the environment: Their occurrence, exposure routes, toxic studies, and potential effects on human health.

Microplastics (MPs) and nanoplastics (NPs) are emerging environmental pollutants, having a major ecotoxicological concern to humans and many other biotas, especially aquatic animals. The physical and chemical compositions of MPs majorly determine their ecotoxicological risks. However, comprehensive knowledge about the exposure routes and toxic effects of MPs/NPs on animals and human health is not fully known. Here this review focuses on the potential exposure routes, human health impacts, and toxicity response of MPs/NPs on human health, through reviewing the literature on studies conducted in different in vitro and in vivo experiments on organisms, human cells, and the human experimental exposure models. The current literature review has highlighted ingestion, inhalation, and dermal contacts as major exposure routes of MPs/NPs. Further, oxidative stress, cytotoxicity, DNA damage, inflammation, immune response, neurotoxicity, metabolic disruption, and ultimately affecting digestive systems, immunology, respiratory systems, reproductive systems, and nervous systems, as serious health consequences.

A review on detection of SARS-CoV-2 RNA in wastewater in light of the current knowledge of treatment process for removal of viral fragments.

The entire globe is affected by the novel disease of coronavirus 2019 (COVID-19 or 2019-nCoV), which is formally recognised as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The World Health Organisation (WHO) announced this disease as a global pandemic. The presence of SARS-CoV-2 RNA in unprocessed wastewater has become a cause of worry due to these emerging pathogens in the process of wastewater treatment, as reported in the present study. This analysis intends to interpret the fate, environmental factors and route of transmission of SARS-CoV-2, along with its eradication by treating the wastewater for controlling and preventing its further spread. Different recovery estimations of the virus have been depicted by the detection of SARS-CoV-2 RNA in wastewater through the viral concentration techniques. Most frequently used viral concentration techniques include polyethylene glycol (PEG) precipitation, ultrafiltration, electronegative membrane, and ultracentrifugation, after which the detection and quantification of SARS-CoV-2 RNA are done in wastewater samples through quantitative reverse transcription-polymerase chain reaction (RT-qPCR). The wastewater treatment plant (WWTP) holds the key responsibility of eliminating pathogens prior to the discharge of wastewater into surface water bodies. The removal of SARS-CoV-2 RNA at the treatment stage is dependent on the operations of wastewater treatment systems during the outbreak of the virus; particularly, in the urban and extensively populated regions. Efficient primary, secondary and tertiary methods of wastewater treatment and disinfection can reduce or inactivate SARS-CoV-2 RNA before being drained out. Nonetheless, further studies regarding COVID-19-related disinfectants, environment conditions and viral concentrations in each treatment procedure, implications on the environment and regular monitoring of transmission need to be done urgently. Hence, monitoring the SARS-CoV-2 RNA in samples of wastewater under the procedure of wastewater-based epidemiology (WBE) supplement the real-time data pertaining to the investigation of the COVID-19 pandemic in the community, regional and national levels.

Influence of air pollution and meteorological factors on the spread of COVID-19 in the Bangkok Metropolitan Region and air quality during the outbreak.

This study investigated the effects of weather conditions, air pollutants, and the air quality index (AQI) on daily cases of COVID-19 in the Bangkok Metropolitan Region (BMR). In this research, we collected data from January 1 to March 30, 2020 (90 days). This study used secondary data of meteorological and air pollutant parameters obtained from the Pollution Control Department of the Ministry of Natural Resources and Environment as well as daily confirmed COVID-19 case data in the BMR obtained from the official webpage of the Department of Disease Control, Ministry of Public Health, Thailand. We employed descriptive statistics, and Spearman and Kendall rank correlation tests were used to investigate the associations of weather variables, air pollutants, AQI with daily confirmed COVID-19 cases. Our findings indicate that CO, NO2, SO2, O3 PM10, PM2.5, AQI have a significantly negative association with daily confirmed COVID-19 cases in the BMR, whereas meteorological parameters such as temperature, relative humidity (RH), absolute humidity (AH) and wind speed (WS) showed significant positive associations with daily confirmed COVID-19 cases in the BMR. Our study is a useful supplement to encourage regulatory bodies to promote environmental strategies, as air pollution regulation could be a sustainable policy for mitigating the harmful effects of air pollutants. Furthermore, this study provides new insights into the relationship between daily meteorological factors, AQI, and air pollutants and daily confirmed COVID-19 cases in the BMR. These data may provide useful information to the public health authorities and decision makers in Thailand, as well as to the World Health Organization (WHO), in order to set proper strategic aimed at reducing the impact of the COVID-19. Future studies concerning SARS-CoV-2 and other viruses should investigate the possibility of infectious droplet dispersion in indoor and outdoor air during and after the epidemic outbreak.

Face mask and medical waste disposal during the novel COVID-19 pandemic in Asia.

The origin of the novel human coronavirus (SARS-CoV-2) and its potential for harm increased face mask and medical waste in the environment, thereby necessitating the urgent prevention and control of the pandemic. The article estimates the face mask and medical waste generation in Asia during the pandemic to convince the waste management and scientific communities to find ways to address the negative impact that the waste disposal has on the environment. Standardisation, procedures, guidelines and strict implementation of medical waste management related to COVID-19, community habitats and public areas should be carefully considered to reduce pandemic risks in hospitals, as proper medical waste disposal effectively controls infection sources.