["When it rains, it pours" - de novo diagnosed multiple myeloma with invasive Streptococcus pneumoniae infection in severe COVID-19 complicated with cytokine storm]. / "A baj nem jár egyedül" ­ de novo diagnosztizált myeloma multiplex invazív Streptococcus pneumoniae fertozéssel citokinviharral szövodött COVID­19-ben.

With the appearance of SARS-CoV-2, the range of infections, considered the most common cause of death for people with multiple myeloma, has expanded. Although the omicron variant (PANGO B.1.1.529) of SARS-CoV-2, that dominates the world at the time of manuscript writing, is less likely to cause fatal infection in immunocompetent patients compared to the delta variant (PANGO B.1.617.2), its transmissibility did not decrease. The likelihood of a severe or critical course of COVID-19 in patients with multiple myeloma is increased by the humoral and cellular immunosuppression caused by the malignancy itself, its targeted hematological treatment, and other comorbidities associated with the disease (e.g., chronic kidney failure). Antiviral therapies, monoclonal antibody preparations used as pre- or post-exposure prophylaxis, and possibly convalescent plasma therapy, started as early as possible might prevent the clinical progression of COVID-19. While the incidence of community-acquired co-infections accompanying COVID-19 in the average population is not exceptionally high, in people with multiple myeloma, Streptococcus pneumoniae infection that follows respiratory viral diseases is approximately 150 times more likely to cause invasive disease. As a result of modern oncohematological treatment, multiple myeloma has now become a chronic disease accompanied by relapses, and those affected should be immunized against the above two pathogens. In our manuscript, we describe the case of an adult patient with severe COVID-19 complicated by cytokine storm and invasive Streptococcus pneumoniae infection who was diagnosed with de novo multiple myeloma during hospital care, and, finally, we briefly review the related literature data. Orv Hetil. 2023; 164(20): 763-769.

Comparison of rainwater quality before and during the MCO using chemometric analyses.

This study aimed to classify the spatiotemporal analysis of rainwater quality before and during the Movement Control Order (MCO) implementation due to the COVID-19 pandemic. Chemometric analysis was carried out on rainwater samples collected from 24-gauge stations throughout Malaysia to determine the samples' chemical content, pH, and conductivity. Other than that, hierarchical agglomerative cluster analysis (HACA) and discriminant analysis (DA) were used to classify the quality of rainwater at each location into four clusters, namely good, satisfactory, moderate, and bad clusters. Note that DA was carried out on the predefined clusters. The reduction in acidity levels occurred in 11 stations (46% of overall stations) after the MCO was implemented. Chemical content and ion abundance followed a downward trend, indicating that Cl- and Na+ were the most dominant among the anions and cations. Apart from that, NH4+, Ca2+, NO3-, and SO42- concentrations were evident in areas with significant anthropogenic activity, as there was a difference in the total chemical content in rainwater when compared before and during the MCO. Based on the dataset before the MCO, 75% of gauge stations were in the good cluster, 8.3% in the satisfactory cluster, 12.5% in the moderate cluster, and 4.2% in the bad cluster. Meanwhile, the dataset during the MCO shows that 72.7% of gauge stations were in the good cluster, 9.1% in the satisfactory cluster, 9.1% in the moderate, and 4.5% in the bad cluster. From this study, the chemometric analysis of the year 2020 rainwater chemical composite dataset strongly indicates that reduction of human activities during MCO affected the quality of rainwater.

Weather extremes associated with increased Ross River virus and Barmah Forest virus notifications in NSW: learnings for public health response.

OBJECTIVE: To examine the sequence of environmental and entomological events prior to a substantial increase in Ross River virus (RRV) and Barmah Forest virus (BFV) notifications with a view to informing future public health response. METHODS: Rainfall, tidal, mosquito and human arboviral notification data were analysed to determine the temporality of events. RESULTS: Following two extremely dry years, there was a substantial increase in the abundance of mosquitoes along coastal New South Wales (NSW) two weeks after a significant rainfall event and high tides in February 2020. Subsequently, RRV and BFV notifications in north east NSW began to increase eight and nine weeks respectively after the high rainfall, with RRV notifications peaking 12 weeks after the high rainfall. CONCLUSIONS: Mosquito bite avoidance messaging should be instigated within two weeks of high summer rainfall, especially after an extended dry period. IMPLICATIONS FOR PUBLIC HEALTH: Intense summertime rain events, which are expected to increase in frequency in south-east Australia with climate change, can lead to significant increases in arboviral disease. These events need to be recognised by public health practitioners to facilitate timely public health response. This has taken on added importance since the emergence of Japanese encephalitis virus in southeastern Australia in 2022.

Abrupt emissions reductions during COVID-19 contributed to record summer rainfall in China.

Record rainfall and severe flooding struck eastern China in the summer of 2020. The extreme summer rainfall occurred during the COVID-19 pandemic, which started in China in early 2020 and spread rapidly across the globe. By disrupting human activities, substantial reductions in anthropogenic emissions of greenhouse gases and aerosols might have affected regional precipitation in many ways. Here, we investigate such connections and show that the abrupt emissions reductions during the pandemic strengthened the summer atmospheric convection over eastern China, resulting in a positive sea level pressure anomaly over northwestern Pacific Ocean. The latter enhanced moisture convergence to eastern China and further intensified rainfall in that region. Modeling experiments show that the reduction in aerosols had a stronger impact on precipitation than the decrease of greenhouse gases did. We conclude that through abrupt emissions reductions, the COVID-19 pandemic contributed importantly to the 2020 extreme summer rainfall in eastern China.

Higher incidence of novel coronavirus (COVID-19) cases in areas with combined sewer systems, heavy precipitation, and high percentages of impervious surfaces.

Combined sewer systems (CSS) are water management systems that collect and transport stormwater and sewer water in the same pipes. During large storm events, stormwater runoff may exceed the capacity of the system and lead to combined sewer overflows (CSOs), where untreated sewer and stormwater are released into the environment. Though current literature reveals inconclusive evidence regarding the infectivity of SARS-CoV-2 in wastewater, detection of infectious SARS-CoV-2 in urine and feces of COVID-19 patients led to concerns that areas contaminated by CSOs may be a reservoir of SARS-CoV-2 and may result in illness after the ingestion and/or inhalation of contaminated splashes, droplets, or aerosols. We investigated the association between COVID-19 incidence and CSSs and whether this association differed by precipitation and percent impervious surfaces as a proxy for possible CSOs. We fitted a quasi-Poisson regression model to estimate the change in percentage of incidence rate of COVID-19 cases in counties with a CSS compared to those without, adjusting for potential confounders (i.e., state, population density, date of first documented COVID-19 case, social vulnerability, and percent vaccinated) and including interaction variables between CSS, precipitation, and impervious surfaces. Our findings suggest that heavy precipitation in combination with high percentages of imperviousness is associated with higher incidences of COVID-19 cases in counties with a CSS compared to in counties without (p-value = 2.5e-9). For example, CSS-counties with precipitation of 10 in/month may observe a higher incidence in COVID-19 cases compared to non-CSS counties if their impervious surfaces exceed 33.5% [95%CI: 23.0%, 60.0%]. We theorize that more COVID-19 cases may be seen in counties with a CSS, heavy precipitation, and high percentages of impervious surfaces because of the possible increase in frequency and severity of CSOs. The results suggest links between climate change, urbanization, and COVID-19.

God is in the rain: The impact of rainfall-induced early social distancing on COVID-19 outbreaks.

We measure the benefit to society created by preventing COVID-19 deaths through a marginal increase in early social distancing. We exploit county-level rainfall on the last weekend before statewide lockdown in the early phase of the pandemic. After controlling for historical rainfall, temperature, and state fixed-effects, current rainfall is a plausibly exogenous instrument for social distancing. A one percent decrease in the population leaving home on the weekend before lockdown creates an average of 132 dollars of benefit per county resident within 2 weeks. The impacts of earlier distancing compound over time and mainly arise from lowering the risk of a major outbreak, yielding large but unevenly distributed social benefit.

Structural equation modeling to shed light on the controversial role of climate on the spread of SARS-CoV-2.

Climate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation among COVID-19, population density, and climate, a theoretical path diagram was hypothesized and tested using structural equation modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of COVID-19 (p < 0.001 and p < 0.01, respectively). Overall, climate outweighs population density (path coefficients: climate vs. incidence = 0.18, climate vs. prevalence = 0.11, population density vs. incidence = 0.04, population density vs. prevalence = 0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of - 0.77, followed by temperature (- 0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p < 0.001. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect the transmission, and their influence may overcome the protective effect of climate, where favourable.

Intraregional propagation of Covid-19 cases in Pará, Brazil: assessment of isolation regime to lockdown.

Due to the high incidence of COVID-19 case numbers internationally, the World Health Organization (WHO) declared a Public Health Emergency of global relevance, advising countries to follow protocols to combat pandemic advance through actions that can reduce spread and consequently avoid a collapse in the local health system. This study aimed to evaluate the dynamics of the evolution of new community cases, and mortality records of COVID-19 in the State of Pará, which has a subtropical climate with temperatures between 20 and 35 °C, after the implementation of social distancing by quarantine and adoption of lockdown. The follow-up was carried out by the daily data from the technical bulletins provided by the State of Pará Public Health Secretary (SESPA). On 18 March 2020, Pará notified the first case of COVID-19. After 7 weeks, the number of confirmed cases reached 4756 with 375 deaths. The results show it took 49 days for 81% of the 144 states municipalities, distributed over an area of approximately 1 248 000 km2 to register COVID-19 cases. Temperature variations between 24.5 and 33.1 °C did not promote the decline in the new infections curve. The association between social isolation, quarantine and lockdown as an action to contain the infection was effective in reducing the region's new cases registration of COVID-19 in the short-term. However, short periods of lockdown may have promoted the virus spread among peripheral municipalities of the capital, as well as to inland regions.

Non-linear link between temperature difference and COVID-19: Excluding the effect of population density.

INTRODUCTION: The spatiotemporal patterns of Corona Virus Disease 2019 (COVID-19) is detected in the United States, which shows temperature difference (TD) with cumulative hysteresis effect significantly changes the daily new confirmed cases after eliminating the interference of population density. METHODOLOGY: The nonlinear feature of updated cases is captured through Generalized Additive Mixed Model (GAMM) with threshold points; Exposure-response curve suggests that daily confirmed cases is changed at the different stages of TD according to the threshold points of piecewise function, which traces out the rule of updated cases under different meteorological condition. RESULTS: Our results show that the confirmed cases decreased by 0.390% (95% CI: -0.478 ~ -0.302) for increasing each one degree of TD if TD is less than 11.5°C; It will increase by 0.302% (95% CI: 0.215 ~ 0.388) for every 1°C increase in the TD (lag0-4) at the interval [11.5, 16]; Meanwhile the number of newly confirmed COVID-19 cases will increase by 0.321% (95% CI: 0.142 ~ 0.499) for every 1°C increase in the TD (lag0-4) when the TD (lag0-4) is over 16°C, and the most fluctuation occurred on Sunday. The results of the sensitivity analysis confirmed our model robust. CONCLUSIONS: In US, this interval effect of TD reminds us that it is urgent to control the spread and infection of COVID-19 when TD becomes greater in autumn and the ongoing winter.

Quantifying the influence of short-term emission reductions on climate.

The COVID-19 (coronavirus disease 2019) pandemic has resulted in a marked slowdown in greenhouse gas and aerosol emissions. Although the resulting emission reductions will continue to evolve, this will presumably be temporary. Here, we provide estimates of the potential effect of such short-term emission reductions on global and regional temperature and precipitation by analyzing the response of an Earth System Model to a range of idealized near-term emission pathways not considered in available model intercomparison projects. These estimates reveal the modest impact that temporary emission reductions associated with the COVID-19 pandemic will have on global and regional climate. Our simulations suggest that the impact of carbon dioxide and aerosol emission reductions is actually a temporary enhancement in warming rate. However, our results demonstrate that even large emission reductions applied for a short duration have only a small and likely undetectable impact.

Climate change: how it impacts the emergence, transmission, resistance and consequences of viral infections in animals and plants.

The ongoing COVID-19 pandemic has made us wonder what led to its occurrence and what can be done to avoid such events in the future. As we document, one changing circumstance that is resulting in the emergence and changing the expression of viral diseases in both plants and animals is climate change. Of note, the rapidly changing environment and weather conditions such as excessive flooding, droughts, and forest fires have raised concerns about the global ecosystem's security, sustainability, and balance. In this review, we discuss the main consequences of climate change and link these to how they impact the appearance of new viral pathogens, how they may facilitate transmission between usual and novel hosts, and how they may also affect the host's ability to manage the infection. We emphasize how changes in temperature and humidity and other events associated with climate change influence the reservoirs of viral infections, their transmission by insects and other intermediates, their survival outside the host as well the success of infection in plants and animals. We conclude that climate change has mainly detrimental consequences for the emergence, transmission, and outcome of viral infections and plead the case for halting and hopefully reversing this dangerous event.

Study design and operational framework for a community-based Malaria Elimination Demonstration Project (MEDP) in 1233 villages of district Mandla, Madhya Pradesh.

BACKGROUND: In the past decade substantial reduction in malaria morbidity and mortality has been observed through well-implemented case management and vector control strategies. India has also achieved a significant reduction in malaria burden in 2018 and has committed to eliminate malaria by 2030. The Mandla Malaria Elimination Demonstration Project (MEDP) was started in 2017 in 1233 villages of District Mandla to demonstrate malaria elimination in a tribal district with hard-to-reach areas was possible using active and passive surveillance, case management, vector control, and targeted information, education and communication campaigns. An operational plan was developed to strengthen the existing surveillance and malaria elimination systems, through fortnightly active case detection to ensure that all cases including those that are introduced into the communities are rapidly identified and treated promptly. The plan also focused on the reduction of human-mosquito contact through the use of Long-Lasting Insecticial Nets (LLINs) and Indoor Residual Spray (IRS). The operational plan was modified in view of the present COVID-19 pandemic by creating systems of assistance for the local administration for COVID-related work while ensuring the operational integrity of malaria elimination efforts. RESULTS: The use of MEDP study design and operational plan, with its built-in management control systems, has yielded significant (91%) reduction of indigenous cases of malaria during the period from June 2017 to May 2020. The malaria positivity rate was 0.33% in 2017-18, 0.13% in 2018-19, and 0.06% in 2019-20. Mass screening revealed 0.18% malaria positivity in September-October 2018, followed by 0.06% in June 2019, and 0.03% in December 2019, and these were mostly asymptomatic cases in the community. The project has been able to sustain the gains of the past three years during the ongoing COVID-19 pandemic. CONCLUSION: This paper provides the study design and the operational plan for malaria elimination in a high-burden district of Central India, which presented difficulties of hard to reach areas, forest malaria, and complex epidemiology of urban and rural malaria. The lessons learned could be used for malaria elimination efforts in rest of the country and other parts of South Asia with comparable demography and epidemiology.

Implications of monsoon season and UVB radiation for COVID-19 in India.

India has recorded 142,186 deaths over 36 administrative regions placing India third in the world after the US and Brazil for COVID-19 deaths as of 12 December 2020. Studies indicate that south-west monsoon season plays a role in the dynamics of contagious diseases, which tend to peak post-monsoon season. Recent studies show that vitamin D and its primary source Ultraviolet-B (UVB) radiation may play a protective role in mitigating COVID-19 deaths. However, the combined roles of the monsoon season and UVB radiation in COVID-19 in India remain still unclear. In this observational study, we empirically study the respective roles of monsoon season and UVB radiation, whilst further exploring, whether the monsoon season negatively impacts the protective role of UVB radiation in COVID-19 deaths in India. We use a log-linear Mundlak model to a panel dataset of 36 administrative regions in India from 14 March 2020-19 November 2020 (n = 6751). We use the cumulative COVID-19 deaths as the dependent variable. We isolate the association of monsoon season and UVB radiation as measured by Ultraviolet Index (UVI) from other confounding time-constant and time-varying region-specific factors. After controlling for various confounding factors, we observe that a unit increase in UVI and the monsoon season are separately associated with 1.2 percentage points and 7.5 percentage points decline in growth rates of COVID-19 deaths in the long run. These associations translate into substantial relative changes. For example, a permanent unit increase of UVI is associated with a decrease of growth rates of COVID-19 deaths by 33% (= - 1.2 percentage points) However, the monsoon season, mitigates the protective role of UVI by 77% (0.92 percentage points). Our results indicate a protective role of UVB radiation in mitigating COVID-19 deaths in India. Furthermore, we find evidence that the monsoon season is associated with a significant reduction in the protective role of UVB radiation. Our study outlines the roles of the monsoon season and UVB radiation in COVID-19 in India and supports health-related policy decision making in India.

A slow rainy season onset is a reliable harbinger of drought in most food insecure regions in Sub-Saharan Africa.

Since 2015, Sub-Saharan Africa (SSA) has experienced an unprecedented rise in acute food insecurity (AFI), and current projections for the year 2020 indicate that more than 100 million Africans are estimated to receive emergency food assistance. Climate-driven drought is one of the main contributing factors to AFI, and timely and appropriate actions can be taken to mitigate impacts of AFI on lives and livelihoods through early warning systems. To support this goal, we use observations of peak Normalized Difference Vegetation Index (NDVI) as an indicator of seasonal drought conditions following a rainy season to show that delays in the onset of the rainy season (onset date) can be an effective early indicator of seasonal drought conditions. The core of this study is an evaluation of the relationship of the onset dates and peak NDVI, stratified by AFI risks, calculated using AFI reports by the United States Agency of International Development (USAID)-funded Famine Early Warning Systems Network (FEWS NET). Several parts of SSA, mostly located in East Africa (EA), reported the "Crisis" phase of AFI-requiring emergency food assistance-at least one-third of the time between April 2011 to present. The results show that the onset date can effectively explain much of the interannual variability in peak NDVI in the regions with the highest AFI risk level, particularly in EA where the median of correlation (across all the Administrative Unit 2) varies between -0.42 to -0.68. In general, an onset date delay of at least 1 dekad (10 days) increases the likelihood of seasonal drought conditions. In the regions with highest risks of AFI, an onset delay of just 1 dekad doubles the chance of the standardized anomaly of peak NDVI being below -1, making a -1 anomaly the most probable outcome. In those regions, a 2-dekads delay in the onset date is associated with a very high probability (50%) of seasonal drought conditions (-1 standardized anomaly of NDVI). Finally, a multivariate regression analysis between standardized anomaly and onset date anomaly further substantiates the negative impacts of delay in onset date on NDVI anomaly. This relationship is statistically significant over the SSA as a whole, particularly in the EA region. These results imply that the onset date can be used as an additional critical tool to provide alerts of seasonal drought development in the most food-insecure regions of SSA. Early warning systems using onset date as a tool can help trigger effective mid-season responses to save human lives, livestock, and livelihoods, and, therefore, mitigate the adverse impacts of drought hazards.