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The objective of this research is to develop a monthly indicator that synthesizes the economic acti-vity of the construction sector in Valle del Cauca, as a tool for analyzing the production cycle and as a single, public measure that contributes to decision-making. Dynamic factorial models, the Kalman filter and the Litterman method are used, also employed in the Monthly Index of Economic Activity (IMAE), in order to capture signals, changes in the productive cycle of construction and compile the sectoral economic facts that affect production. In the results, the dynamics of the sectoral and economic variables are observed that explain the behavior of the sector in Valle del Cauca during 2009-2020. A change of slope is observed in 2020, as a direct consequence of the crisis generated by COVID-19 and the restrictive measures taken by the government to contain its advance.
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This paper documents the short-run macroeconomic impacts of influenza pandemics across 16 countries spanning 1871-2016 using the Jordà-Schularick-Taylor Macrohistory Database and the Human Mortality Database. We find pandemic-induced mortality contributed meaningfully to business cycle fluctuations in the post 1870 era. We identify negative causal impacts on the cyclical component of GDP using pandemics to instrument for working-age mortality. The analysis of short-run economic outcomes extends literature dominated by long-run economic growth outcomes and case studies of several specific health shocks such as the Black Death, Spanish Flu or COVID-19. Our findings illustrate that less catastrophic pandemics still have important economic implications.
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The importance of food supply throughout the world has once again shown its significance in the COVID-19 pandemic period. A continuous food supply is possible with correct agricultural programming. An effective agricultural product programming can only be possible by obtaining precise agricultural data. However, it is very difficult to gather accurate agricultural production statistics from all over the world and confirm their accuracy. In this study, the compatibility of the production statistics of six important agricultural products (wheat, rice, potato, onion, banana, apple) which had been collected from local sources, and had published as opensource by the Food and Agriculture Organization of the United Nations, with Benford's law was examined for the first time. Data for the last two decades are used to ignore the impact of annual fluctuations. The compatibility of theoretically expected and observed data was tested by Chi-square (X2) and Mean Absolute Deviation (MAD) tests. Although inconsistencies were found in some data by examining the numbers in the first, second, and first two digits, in general, the MAD test results gave a mostly concordant result.
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This paper establishes electricity consumption as an indicator for tracking economic fluctuations in Bangladesh. It presents monthly data on national electricity consumption since 1993 and subnational daily consumption data since February 2010. Electricity consumption is strongly correlated with other high-frequency indicators of economic activity, and it has declined during natural disasters and the COVID-19 lockdowns. The paper estimates an electricity consumption model that explains over 90% of the variation in daily consumption based on a quadratic trend, seasonality, within-week variation, national holidays, Ramadan, and temperature. Deviations from the model prediction can act as an indicator of subnational economic fluctuations. For example, electricity consumption in Dhaka fell around 40% below normal in April and May 2020 during the first COVID-19 lockdown and remained below normal afterwards. The later lockdowns, in contrast, had much smaller impacts, in line with less stringent containment measures and more effective adaptation.
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This study examines how the relationship between oil and stock market return of BRICS behaves at different investment horizons. Using data ranging from 2006 to 2020, the wavelet and MGARCH-DCC found that the stock markets' return of Russia, Brazil, and South Africa are comparatively more correlated with oil price return across the investment horizons and more volatile particularly during the Covid-19 period. However, the stock markets' return of China and India is less correlated with oil price return and less volatile. It is also revealed that oil price return leads the BRICS' stock markets' return and both are positively correlated.
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The objective of this research is to develop a monthly indicator that synthesizes the economic acti-vity of the construction sector in Valle del Cauca, as a tool for analyzing the production cycle and as a single, public measure that contributes to decision-making. Dynamic factorial models, the Kalman filter and the Litterman method are used, also employed in the Monthly Index of Economic Activity (IMAE), in order to capture signals, changes in the productive cycle of construction and compile the sectoral economic facts that affect production. In the results, the dynamics of the sectoral and economic variables are observed that explain the behavior of the sector in Valle del Cauca during 2009-2020. A change of slope is observed in 2020, as a direct consequence of the crisis generated by COVID-19 and the restrictive measures taken by the government to contain its advance.
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The indoor climate of non-climatized churches is usually subject to cyclical fluctuations of temperature and relative humidity induced by external climate conditions which might be dampened by the high thermal capacity of their envelope. However, several phenomena affect their indoor climate (e.g., internal gains due to people and artificial lighting, air infiltration, etc.), which lead to environmental variations that might jeopardize the artworks contained within. In particular, one of the most influential parameters that may affect non-climatized churches is the massive and intermittent presence of people who constantly visit their spaces. In such regard, long-term monitoring allows the collection of environmental data with different building operation conditions and visitor fluxes. This paper analyses the indoor climate of the Milan Cathedral (Duomo di Milano) in Italy for three continuous years (including the lockdown period that occurred in 2020 caused by the COVID-19 pandemic), with a focus on visitors' effects on the indoor environment and the conservation of the main artworks contained within. The results of the analysis have shown that spaces with huge volume are most influenced by the opening of the doors rather than the hygrothermal contribution of the intermittent presence of massive crowds. Moreover, the absence of visitors for a prolonged period correlates with an improvement in the indoor conservation conditions for artworks, especially those made of hygroscopic materials, due to the reduction in short, rapid climate fluctuations.
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To analyze the population density, seasonal fluctuation of Aedes albopictus in Haizhu District, Guangzhou from 2017 to 2021, so as to provide a scientific basis for the monitoring and prevention and control of mosquito vector density of dengue fever. The data of dengue fever cases and Aedes surveillance data in Haizhu District, Guangzhou from 2017 to 2021 were collected, and the data of 2017-2019 and 2020-2021 were grouped to compare and analyze the characteristics of dengue epidemic and the density fluctuation of Aedes mosquitoes. A total of 517 dengue cases were reported in Haizhu District, Guangzhou from 2017 to 2021, of which only 7 cases were reported from 2020 to 2021, and the peak period of reported cases every year was August to November. Before the COVID-19 pandemic, there was a positive correlation between the number of local cases and the number of imported cases(rs=0.63, P<0.05) and BI(rs=0.73, P<0.05). The peak density of Aedes was from May to October, and the differences of mean BI(X~2=1 143.40,P<0.001), MOI(X~2=188.30,P<0.001), and SSI(X~2=4 499.43,P<0.001)before and after the COVID-19 pandemic were statistically significant. In general, before and after the COVID-19 pandemic, the density of Aedes in high-risk areas was higher than that in low-risk areas. After COVID-19 pandemic, the number of reported cases and the density of Aedes in Haizhu District decreased, but the density of Aedes in the high-risk area was still higher than that in low-risk areas, and a certain risk of outbreak still existed, so the government should continue to take more precise measures to strictly prevent dengue epidemic.
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This article examines macroeconomic effects and transmission mechanisms of Covid-19 in Mongolia, a developing and commodity-exporting economy, by estimating a Bayesian structural vector autoregression on quarterly data. We find strong cross-border spillover effects of Covid-19 passing through changes in commodity markets and the Chinese economy. Our estimates suggest that China's GDP and copper price shocks respectively account for three-fifths and one-fifths of the drop in real GDP in 2020Q1. The recovery observed for 2020Q2-2021Q1 is primarily due to positive external shocks. However, disruptions in credit and labor markets have been sustained in the economy. Two-thirds of the fall in employment in 2021Q1 could be attributed to adverse labor demand shocks. We also reveal novel empirical evidence for the balance sheet channel of the exchange rate, the financial accelerator effects, and an indirect channel of wage shock to consumer price passing through bank credit.
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The research mainly aimed to study the impact of the economic reform policy and the Corona pandemic and seasonal factors on the prices of the most important Egyptian agricultural exports and imports. The most important results were the following: - By studying the trend analysis of the monthly average of the prices of the most important exported and imported commodities, it shows the real price increase over time per month for the exports of 17 commodities represented as "olive oil, dried fruits, Rumi cheese, aromatic oils and resins, dried onions, processed cheese, dried vegetables, white cheese, juices." Its foundations are oily seeds and fruits, onions and garlic, citrus fruits, preserved strawberries, frozen artichokes, processed potatoes, frozen vegetables, and potatoes. - Also found was that the economic reform policy had a statistically significant effect on the average real price of the exports of the 17 commodities under study, as well as the imports of meat, oils, sugar, beans, and wheat, in addition to the imports of the most important production requirements studied, such as seeds, pesticides, disinfectants, and fertilizers. that during the study period. - By studying the impact of the COVID-19 crisis on the real monthly prices of exports and imports of the commodities under study, it was found that the average monthly price decreased in real prices for all commodities under study, except for oils and aromatic resins, but the statistical significance of the rates of decrease during the study period did not prove.
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The observations of atmospheric CO2 mole fraction in urban area in China are relative sparse. Here, we present the first-hand observation of atmospheric CO2 mole fraction from 2016 to 2020 at a city station (Hangzhou, abbreviated as HZ) in the Yangtze River Delta, which is one of the strongest CO2 source regions in China. The CO2 mole fraction at an adjacent World Meteorological Organization / Global Atmospheric Watch (WMO/GAW) programme site (Lin'an, LAN) are also presented and compared. The temporal variations, seasonal variations, and influence of COVID-19 pandemic are analyzed. Our results show that, the variations of CO2 mole fraction in Hangzhou are mainly driven by the local emissions, both atmospheric dilution conditions (i.e., wind speed, visibility) and topography, and the temporal variations are apparently different with the suburb site of LAN, although the distance between the two stations is only 50 km. During the observation period, the CO2 mole fraction at HZ is on average 15.6 +or- 0.2 ppm higher than LAN, with two distinct peaks observed at 9:00 and 17:00-18:00, corresponding to traffic rushing hours. The growth rate of atmospheric CO2 mole fraction is 11.2 +or- 0.1 ppm yr-1 before the COVID-19 pandemic (from 2016 to 2019), which is much higher than the suburb site of LAN, 5.4 +or- 0.1 ppm yr-1. The COVID-19 pandemic has led to a plunge of atmospheric CO2 mole fraction at HZ in 2020, with a value of 15.7 +or- 0.7 ppm, corresponding to 3.5% lower than the year of 2019. But at LAN, the annual average CO2 mole fraction in 2020 is 1.5 +or- 0.5 ppm higher than the previous year, similar to the trend in the northern hemisphere. The different annual CO2 mole fraction growth rate at HZ indicates that the CO2 mole fraction at Hangzhou may be dominated by local anthropogenic emissions, despite the transport of airmass from the north and southwest.
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To analyze the epidemiological characteristics and related factors of norovirus in Guangxi from 2015 to 2020, and to provide scientific recommendations for norovirus prevention and control. Methods The foodborne diseases surveillance data were collected from 11 sentinel hospitals through the National Foodborne Disease Monitoring and Reporting System from 2015 to 2020. R software with version 4.0.3 was used for descriptive and statistical analysis, including epidemic curve, chi-square test, and trend chi-square and so on. Logistic regression was used to analyze norovirus-related factors, OR values and 95% confidence intervals were calculated respectively with the statistical test level of P < 0.05. Results There were 1 008 norovirus cases detected, with a detection rate of 12.75% (1 008/7 903). Children with age less than 5 years (OR=1.43, 95%CI: 1.13-1.82) and patients at age 20-45 (OR=1.45, 95%CI: 1.13-1.87) were high risk population. The detection rate was higher in autumn (OR=1.29, 95%CI: 1.08-1.53) but lower in summer (OR=0.67, 95%CI: 0.55-0.80). In addition, the tourist area (Guilin City) presented a higher detection rate than other areas (OR=1.41, 95%CI: 1.10-1.80). Aquatic products (OR=1.40, 95%CI: 1.03-1.91), meat and dairy products (OR=1.31, 95%CI: 1.06-1.61) were high-risk foods for norovirus infection. The prevention and control policies of COVID-19 can reduce the possibility of norovirus by 61% (OR=0.39, 95%CI: 0.31-0.49) showed a declining trend (Trend X2=85.33, P < 0.001). In addition, prolonged visit time can lead to 19%-23% decrease in the detection rate of norovirus (OR24-48 hours=0.81, 95%CI: 0.70-0.95;OR>48 hours=0.77, 95%CI: 0.63-0.93). Conclusions The epidemic of norovirus presented seasonal and regional distribution in Guangxi with a declining detection rate trend in diarrhea patients during recent 6 years. Young children were high-risk population in infection norovirus. The intake of seafood can increase the risk of norovirus infection. The prevention and control policies of COVID-19 can sharply decrease the possibility of infection norovirus. The monitoring of key foods such as seafood should be strengthened, and the early screening of suspected cases should be taken. The norovirus monitoring should be improved to ensure the health of the population.
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In recent years, international crude oil prices have been subject to unusually high fluctuations due to the ravages of the COVID-19 epidemic. Under such extreme market conditions, online investor sentiment can strengthen the correlation between oil price changes and external events. We use a (rolling-window) structural vector autoregression method to investigate the dynamic impact of online investor sentiment on WTI crude oil prices before and after the COVID-19 pandemic across multiple topics of price, supply, demand, and so on, which aims to explore the fluctuation mechanism driven by sentiment and the price changes triggered by public health events. The proposed aspect-level sentiment analysis approach can effectively distinguish and measure sentiment scores of different aspects of the oil market. Our results show that the constructed oil price prosperity index contributes 49.84% to the long-term fluctuations of WTI oil price, ranking first among the influencing factors considered. In addition, the peak value of impulse shocks to WTI oil prices rose from 6.47% to 8.40% during the period of dramatic price volatility caused by the epidemic. The results sketch the mechanisms by which investor sentiment can affect crude oil prices, which help policymakers and investors protect against extreme risks in the oil market. © 2023 Elsevier Ltd
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From 2017 to 2020, 1 078 piglet diarrhea samples were collected from 6 pig farms in different districts of Shanghai. Multiple RT-PCR method was used for detection and analysis to study the infection status of bovine viral diarrhea virus (BVDV) in swinery in Shanghai. The results showed that the overall detection rate of BVDV in swinery in Shanghai was 7.14% (77/1 078), and showed an increasing trend year by year. The mixed infection rate of BVDV and other diarrhea pathogens was high, with the highest dual infection rate (65%, 26/40), mainly BVDV/PASTV (61.54%, 16/26). On this basis, the triple infection rate was 25% (10/40), mainly BVDV/PAStV/PKoV (40%, 4/10) infection mode;The quadruple infection rate was 10% (4/40), which was dominated by BVDV/PAStV/PEDV/PSV (50%, 2/4) infection. The BVDV prevalence in swinery was seasonal, and the prevalence in spring (10.36%) and autumn (13.59%) was higher than that in summer (6.8%) and winter (2.66%). The positive rate of BVDV in different pig farms was significantly different by 0-24.07%. In view of the detection rate of diarrhea virus dominated by PEDV in pig farm 2 had been high in recent years, this study further monitored the infection of BVDV in this pig farm, and found that the detection rate of BVDV in this pig farm was increasing year by year from 2017 to 2019, with the highest detection rate in 2019 (8.61%, 42/488);The mixed infection of BVDV and other diarrhea pathogens was also serious, with the dual infection rate of 57.58% (19/32), triple infection rate of 21.21% (7/32), quadruple infection rate of 21.21% (7/32), respectively. This study enriched the epidemic data of BVDV in swinery in Shanghai, and could provide reference for the prevention and control of pig epidemics.
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The objective of this work is to assess the effect of implementing countercyclical macroprudential regulation in Mexico with the objective of verify whether this type of policy is welfare-improving. Using a DSGE model, two kinds of macroprudential rules are tested: countercyclical bank capital requirements and countercyclical loan-to-value ratios. Results suggest that these rules are welfare-improving and avoid the formation of credit bubbles as well as facilitate loans in the presence of macroeconomic crises. Results suggest that the use of countercyclical rules is effective in keeping the debt level according to its long-term equilibrium. This paper presents a theoretical framework to analyze banking regulation for policy purposes and is the first attempt to analyze countercyclical regulation in Mexico using a microfounded model. Results can be used to rationalize the use of macroprudential tools during the COVID‑19 pandemic given the current interventions in the Mexican banking system. © 2021 The Author(s).
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In extraordinary situations, like the Covid-19 pandemic, irregular demand fluctuations can hardly be predicted by traditional forecasting approaches. Even the current extent of decline of demand is typically unknown since tourism statistics are only available with a time delay. This study presents an approach to benefit from user generated content (UGC) in form of online reviews from TripAdvisor as input to estimate current tourism demand in near real-time. The approach builds on an additive time series component model and linear regression to estimate tourist arrivals. Results indicate that the proposed approach outperforms a traditional seasonal naïve forecasting approach when applied to a period of extraordinary demand fluctuations caused by a crisis, like Covid-19. The approach further enables a real-time monitoring of tourism demand and the benchmarking of tourism business in times of extraordinary demand fluctuations. © 2023, The Author(s).
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In this paper, we investigate the Casimir effect within a virus RNA, particularizing the study to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Then, we discuss the possibility of occurring damage or mutation in its genome due to the presence of quantum vacuum fluctuations inside and around the RNA ribbon. For this, we consider the geometry and the nontrivial topology of the viral RNA as having a simple helical structure. We initially compute the non-thermal Casimir energy associated to that geometry, considering boundary conditions that constrain the zero point oscillations of a massless scalar field to the cylindrical cavity containing a helix pitch of RNA ribbon. Then we extend the obtained result to the electromagnetic field and, following, we calculate the probability of occurring damage or mutation in RNA by using the normalized inverse exponential distribution, which suppresses very low energies, and consider cutoff (threshold) energies corresponding to UV-A and UV-C rays, surely responsible by mutations. Then, by taking into account UV-A, we arrive at a mutation rate per base per infection cycle, which in the case of the SARS-CoV-2 is non-negligible. We find a maximum value of this mutation rate for an RNA ribbon radius, applying it for SARS-CoV-2, in particular. We also calculate a characteristic longitudinal oscillation frequency for the helix pitch value corresponding to the local minimum of the Casimir energy. Finally, we consider thermal fluctuations of classical and quantum nature and show that the corresponding probability of mutation is completely negligible for that virus. Therefore, we conclude that only the nontrivial topology and the geometric attributes of the RNA molecule contribute to the possible mutations caused by quantum vacuum fluctuations in the viral genome.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/genetics , Mutation , Mutation Rate , RNA, Viral/genetics , RNA, Viral/chemistryABSTRACT
We present the CarbonTracker Europe High-Resolution (CTE-HR) system that estimates carbon dioxide (CO2) exchange over Europe at high resolution (0.1 × 0.2∘) and in near real time (about 2 months' latency). It includes a dynamic anthropogenic emission model, which uses easily available statistics on economic activity, energy use, and weather to generate anthropogenic emissions with dynamic time profiles at high spatial and temporal resolution (0.1×0.2∘, hourly). Hourly net ecosystem productivity (NEP) calculated by the Simple Biosphere model Version 4 (SiB4) is driven by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) dataset. This NEP is downscaled to 0.1×0.2∘ using the high-resolution Coordination of Information on the Environment (CORINE) land-cover map and combined with the Global Fire Assimilation System (GFAS) fire emissions to create terrestrial carbon fluxes. Ocean CO2 fluxes are included in our product, based on Jena CarboScope ocean CO2 fluxes, which are downscaled using wind speed and temperature. Jointly, these flux estimates enable modeling of atmospheric CO2 mole fractions over Europe.We assess the skill of the CTE-HR CO2 fluxes (a) to reproduce observed anomalies in biospheric fluxes and atmospheric CO2 mole fractions during the 2018 European drought, (b) to capture the reduction of anthropogenic emissions due to COVID-19 lockdowns, (c) to match mole fraction observations at Integrated Carbon Observation System (ICOS) sites across Europe after atmospheric transport with the Transport Model, version 5 (TM5) and the Stochastic Time-Inverted Lagrangian Transport (STILT), driven by ECMWF-IFS, and (d) to capture the magnitude and variability of measured CO2 fluxes in the city center of Amsterdam (the Netherlands).We show that CTE-HR fluxes reproduce large-scale flux anomalies reported in previous studies for both biospheric fluxes (drought of 2018) and anthropogenic emissions (COVID-19 pandemic in 2020). After applying transport of emitted CO2, the CTE-HR fluxes have lower median root mean square errors (RMSEs) relative to mole fraction observations than fluxes from a non-informed flux estimate, in which biosphere fluxes are scaled to match the global growth rate of CO2 (poor person's inversion). RMSEs are close to those of the reanalysis with the CTE data assimilation system. This is encouraging given that CTE-HR fluxes did not profit from the weekly assimilation of CO2 observations as in CTE.We furthermore compare CO2 concentration observations at the Dutch Lutjewad coastal tower with high-resolution STILT transport to show that the high-resolution fluxes manifest variability due to different emission sectors in summer and winter. Interestingly, in periods where synoptic-scale transport variability dominates CO2 concentration variations, the CTE-HR fluxes perform similarly to low-resolution fluxes (5–10× coarsened). The remaining 10 % of the simulated CO2 mole fraction differs by >2 ppm between the low-resolution and high-resolution flux representation and is clearly associated with coherent structures ("plumes”) originating from emission hotspots such as power plants. We therefore note that the added resolution of our product will matter most for very specific locations and times when used for atmospheric CO2 modeling. Finally, in a densely populated region like the Amsterdam city center, our modeled fluxes underestimate the magnitude of measured eddy covariance fluxes but capture their substantial diurnal variations in summertime and wintertime well.We conclude that our product is a promising tool for modeling the European carbon budget at a high resolution in near real time. The fluxes are freely available from the ICOS Carbon Portal (CC-BY-4.0) to be used for near-real-time monitoring and modeling, for example, as an a priori flux product in a CO2 data assimilation system. The data are available at 10.18160/20Z1-AYJ2 .
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Quantifying risk spillovers from exchange rates to inbound tourist arrivals by purpose of visit is essential for Australia to take proactive measures to achieve tourism business recovery and resilience after such critical events like the recent bushfires and the COVID-19 pandemic. Using a monthly dataset over the period January 1998–March 2020, this paper calculates the conditional value-at-risk (CoVaR) to evaluate how different types of inbound tourists to Australia respond to exchange rate fluctuations. The empirical results identify inbound tourist arrivals with the highest sensitivity to exchange rate fluctuations, confirming the role of exchange rates in determining inbound tourist arrivals by purpose of visit. Furthermore, these results shed light on provisions of tourism products, services, and infrastructural facilities to satisfy different requirements of Australia's inbound tourists by purpose of visit, aiming to promote tourism business recovery and resilience in Australia.