Daily Counts Research Articles

Photocatalytic glucose depletion and hydrogen generation for diabetic wound healing

High-glucose microenvironment in the diabetic foot ulcer (DFU) causes excessive glycation and induces chronic inflammation, leading to the difficulty of DFU healing. Hydrogen-rich water bath can promote the healing of DFU in clinic by virtue of the anti-inflammatory effect of hydrogen molecules, but the long-term daily soaking counts against the formation of a scab and cannot change the high-glucose microenvironment, limiting the outcome of DFU therapy. In this work, photocatalytic therapy of diabetic wound is proposed for sustainable hydrogen generation and local glucose depletion by utilizing glucose in the high-glucose microenvironment as a sacrificial agent. Hydrogen-incorporated titanium oxide nanorods are developed to realize efficient visible light (VIS)-responsive photocatalysis for glucose depletion and hydrogen generation, achieving a high efficacy of diabetic wound healing. Mechanistically, local glucose depletion and hydrogen generation jointly attenuate the apoptosis of skin cells and promote their proliferation and migration by inhibiting the synthesis of advanced glycation end products and the expression of their receptors, respectively. The proposed VIS-photocatalytic strategy provides a solution for facile, safe and efficient treatment of DFU.

Examination of the Temporal Stability of Daily and Monthly Adjustment Factors of Bicycle Traffic

Monthly adjustment factors (MFs) and daily adjustment factors (DFs) are typically calculated using complete annual data from permanent count stations. These factors are applied at other locations where short-term counts are collected using temporary counters. In this research, the long-term temporal stability of MFs and DFs for bicycle traffic was investigated. Annual daily count data collected from permanent count stations in Vancouver, Canada between 2010 and 2019 were used in the study. A longitudinal analysis of MFs and DFs in the 10 years was undertaken. The coefficient of variation (CoV) of the MFs of the 10 years was found to be less than 12% for the months between April and September, indicating the potential temporal transferability of these factors from one year to a future year. The other 4 months of the year showed a higher CoV with December being the highest (i.e., 25%). As for the DFs, it was found that, depending on the day of week, weather, and month, substantial variation could exist in the calculated factors. Nevertheless, factors developed for dry weekdays in the summer months were shown to exhibit the lowest variability over the 10 years and as such these factors were deemed transferable from one year to another. The results presented in this paper could be beneficial for transportation planners and traffic engineers managing traffic monitoring programs of cycling traffic for which the potential for transferring historical adjustment factors to future years was demonstrated.

Short-term effects of particulate matter and desert dust on mortality in Southern Europe, the Middle East and Eastern Asia

Background: Desert dust represents a threat to health, but the evidence is limited, as past studies were localised and adopted different exposure metrics and/or statistical approaches. We aim to evaluate the short-term effects of desert dust episodes and particulate matter (PM) on natural mortality in multiple cities from different geo-climatic zones. Methods: Daily death counts were collected for 21 cities in southern Europe (France, Greece, Italy, Portugal, Spain), the Middle East (Iran, Kuwait) and Eastern Asia (China, Japan, South Korea, Taiwan) from 2003-2018. Dust advection days were identified using satellite data, operational models and back-trajectories. Daily mean concentrations of PM10 (PM<10µm) and PM2.5 (<2.5µm) were available for 21 and 16 cities, respectively. City-specific quasi-Poisson regression models were fitted, adjusted for time trends and meteorology, and city-specific estimates were combined using random-effects meta-analysis. Results: The frequency of dust days ranged from 5% in Northern Italy to 61% in Northern China, with highest levels of PM10 and PM2.5 raised in Kuwait (191 µg/m3) and Xian (182 µg/m3). Overall, dust (yes/no), PM10 and PM25 (10 µg/m3) increased mortality at the same day by 0.52% (95% confidence interval: 0.04, 1.01), 0.14% (0.07,0.21) and 0.16% (0.02, 0.31), respectively. We found differential effects of PM on non-dust versus dust days: on non-dust days 10 µg/m3 increases in PM10 and PM25 increased mortality by 0.20% (0.11, 0.29) and 0.26% (0.05, 0.46) in non-dust days, while in dust days they increased mortality by 0.06% (95% confidence interval: 0.01, 0.10) and 0.05% (-0.04, 0.15), respectively. Conclusions: Desert dust may have independent adverse health effects. Further investigation is needed to disentangle the complex role of dust on air quality and health. On-going analyses on a broader set of cities within the MCC network provide a promising opportunity for this purpose. Key words: Desert dust; particulate matter; short-term effects; mortality

Wildfire exposure and health care use among people who use durable medical equipment in Southern California

Background: Climate change-induced wildfires cause trauma, stress, and injury in affected communities, while exposing 70% of the US population to smoke particulate matter (PM2.5) annually and exacerbating cardiorespiratory disease. Few studies examine wildfire smoke exposure in vulnerable populations, and none evaluate residence near a fire. Methods: We identified 236,732 Kaiser Permanente Southern California members who used electricity-dependent durable medical equipment (DME). DME use is associated with respiratory illness and disability, indicating vulnerability to smoke exposure and difficulty evacuating disaster zones. Daily counts of outpatient, inpatient, and emergency healthcare visits made by DME users from 2016-2020 were linked with daily estimates of wildfire generated PM2.5 by residential ZIP code. We used historical maps to identify ZIPs within 20 km of the the 2018 and 2019 Getty and Woolsey fires. We performed negative binomial regression analyses using direct and lagged effects of wildfire PM2.5 and difference-in-differences analyses to evaluate the association between direct wildfire exposure and health care visit frequency. We adjusted for temperature, temporal effects, non-wildfire PM2.5, and spatial confounders. Results: Residence within 20 km of the Woolsey Fire was associated with fewer outpatient and more inpatient visits (RR = 0.98, 95% CI: 0.78, 0.87, RR = 1.45, 95% CI: 1.01, 2.11), while Getty Fire evacuation exposure was not associated with visit frequency. In contrast, increases in wildfire PM2.5 were associated with small and constant increases in outpatient visits 2-6 days after a change. Wildfire PM2.5 was not associated with frequency of inpatient or emergency visits at any lag. Conclusion: DME users, presumed vulnerable to wildfire smoke exposure, may have sheltered in place during fires or took other precautions. However, the Woolsey Fire (which was 10 times larger than the Getty) may have produced health concerns in those directly affected when evacuation was necessary and sheltering in place impossible.

Short-term heat effects on cardiopulmonary morbidity using national small area data – Results of the EXHAUSTION project

BACKGROUND AND AIM: Short-term associations between heat and cardiopulmonary morbidity have been examined mostly in major cities. Given potential differences in the effects of heat between urban and rural areas, it is important to analyze areas of various degrees of urbanization to better understand the health effects of heat. This study investigated heat effects on cardiopulmonary hospital admissions in the warm season (May-September) in Italy and Germany at the small-area level. METHODS: Daily counts of cardiovascular and respiratory hospital admissions were obtained for each municipality in Italy (2001–2015) and Germany (2000–2016). Spatio-temporal models estimated daily mean air temperatures at the municipality level. In each municipality-aggregated district, we first assessed heat effects at lag 0-1 days using district-specific Poisson regression with adjustment for a 4-way interaction between municipality, year, month, and day of the week, using the distributed lag non-linear model approach. Multivariate meta-analysis was then applied to pool the district-specific estimates in each country. Effect modification by age and sex was examined in subgroup analyses. RESULTS: For an increment in daily temperature from the 75th to the 99th percentile, the risk for respiratory hospital admissions increased in both Italy [pooled risk ratio (RR): 1.112, 95% CI: 1.098-1.126] and Germany (pooled RR: 1.074, 95% CI: 1.067-1.081). We did not observe adverse heat effects on cardiovascular hospital admissions in either country. The heat effects on respiratory hospital admissions were stronger in the elderly (75+ years) and females. CONCLUSIONS: Our study provides evidence for an adverse heat effect on respiratory morbidity, which was stronger in Italy with lower latitude. In both countries, the observed heat effects were more prominent in the elderly and females. Further analyses are ongoing to disentangle effects between urban and rural areas. KEYWORDS: air temperature, heat, cardiopulmonary hospital admissions, small area

Short-term effects of heat on respiratory mortality and morbidity in Germany – small-area analysis in the framework of the EXHAUSTION project

Background and Aim: Short-term associations between heat and respiratory mortality and morbidity have been well recognized. However, most studies were conducted in major cities, whereas evidence for more rural areas is limited. In this study, we assessed the short-term associations between air temperature and cause-specific respiratory mortality and hospital admissions in the warm season (May-September) in Germany at a small-area level. Methods: Daily counts of mortality and hospital admissions for respiratory diseases, chronic obstructive pulmonary disease, asthma, lower respiratory tract infections, and pneumonia from 2000 to 2016 were obtained for Germany at the small-area level. Small areas were defined as districts for mortality data and municipalities for hospital admission data. Daily mean air temperatures estimated by a spatio-temporal model were assigned to each small area. We first applied small area-specific Poisson regression allowing for overdispersion, using Distributed Lag Non-linear Models to assess the heat effects at lag 0-1 days (average of same- and previous-day temperatures). Random-effects meta-analysis was then used to pool the small area-specific estimates. Besides, we conducted subgroup analyses to investigate effect modification by age and sex. Results: We observed increased risks for all investigated cause-specific respiratory mortality and hospital admissions associated with heat. The strongest heat effect was found for pneumonia. For an increment from the 75th to the 99th percentile of the temperature distribution, the pooled risk ratio was 1.49 (95% CI: 1.42, 1.57) for pneumonia mortality and 1.20 (95% CI: 1.19, 1.22) for pneumonia hospital admissions. The heat effects were stronger among the elderly (75+ years) and females. Conclusions: Using data from both urban and rural areas, our study suggests the adverse heat effects on respiratory mortality and morbidity in the warm season in Germany. These heat effects were more pronounced among the elderly and females. Keywords: Air temperature, heat, respiratory, mortality, hospital admissions

Ambient temperature and preterm birth risk in New York City: A time-series analysis

BACKGROUND AND AIM Recent studies suggest an association between daily variation in ambient temperature during pregnancy and preterm birth (PTB). Our objective is to examine the short-term effects of heat and cold on PTB risk from 2008 to 2016 in New York City (NYC). METHODS We applied quasi-Poisson regression with distributed lag nonlinear models to estimate the cumulative relative risk (CRR) of daily counts of spontaneous PTB (<37 weeks gestation) and outdoor temperature, and to estimate the fraction of PTBs attributable to temperature, by season, using NYC Vital Statistics birth records and National Weather Service daily temperature data at LaGuardia airport. Models were adjusted for within-season trends and daily number of pregnant people at risk for preterm delivery. Heat and cold were defined as the 95th versus 50th percentile of maximum temperature during the warm season and 5th versus 50th percentile of minimum temperature during the cold season, respectively. Maternal race/ethnicity was assessed for effect modification. RESULTS Our analysis consisted of 38,593 spontaneous PTBs. Heat was not associated with PTB during the warm season [CRR: 0.98 (95% CI: 0.92, 1.05)]. There was a nonlinear association between cold and PTB. During the cold season, the CRR was 1.08 (0.99, 1.17) for cold up to three days before delivery (lag 0-3). The estimated fraction of PTBs attributable to cold was 9.3% (-0.6%, 17.4%), which corresponded to 81 (-2, 154) cold-attributable PTBs over the 9-year study period. Among non-Hispanic Blacks, the CRR was 1.20 (1.04, 1.39) for cold over lag 0-3 days, and an estimated 23.2% (10.3%, 34.3%) of non-Hispanic Black PTBs, equivalent to 69 (29, 105) PTBs, were attributable to cold. CONCLUSIONS Heat had no measurable impact. Cold potentially increased risk of PTB. Our finding for the impact of cold on non-Hispanic Black PTBs warrants additional research. KEYWORDS Preterm birth Temperature

Short-term heat effects and effect modification by ambient air pollution on cardiovascular and respiratory mortality across 148 cities from 13 European countries – Results of the EXHAUSTION project

Background and Aim: Epidemiological evidence on the potential interactive effects of high air temperature and air pollution on cause-specific mortality remains inconclusive and limited to selected locations. We investigated the effects of temperature on cardiovascular and respiratory mortality and its effect modification by particulate matter with a diameter ≤ 2.5 µm [PM₂.₅] and ozone [O₃] during summer months (May-September) in 148 cities across 13 European countries. Methods: For these cities, we obtained daily counts of cardiovascular and respiratory mortality and daily exposure data between 2000 and 2018. We used location-specific confounder-adjusted Quasi-Poisson regression with a tensor product between air temperature and the air pollutant. We extracted temperature estimates at low, medium, and high levels of pollutants defined as the 5th, 50th, and 95th percentile of location-specific air pollutant concentrations. A random-effects multilevel meta-analytical model was used to derive the country-specific and overall estimates. Results: High summer temperatures were associated with increased cardiovascular and respiratory mortality. We further observed modification of the heat effects by elevated levels of PM₂.₅ and O₃ in most locations, with stronger effects for respiratory than cardiovascular mortality. For example, the percent increase in respiratory mortality per increase in the 2-day average summer temperature from the 75th to the 99th percentile was 9.2% (95% Confidence Interval [CI] 8.9-9.4), 13.0% (95% CI 12.8, 13.2), and 19.8% (95% CI 19.5, 20.2) at low, medium, and high levels of PM₂.₅, respectively. Conclusion: We observed significant modification of the heat effects by elevated levels of PM₂.₅ and O₃ leading to an increased risk of cardiovascular and respiratory mortality. With both temperature and air pollutant concentrations foreseen to increase considering climate change, targeted adaptation and mitigation measures are crucial to enhance resilience and sustainable development in alignment with EU climate change policies. Keywords: Air temperature, air pollution, cause-specific mortality, effect modification, Europe

Urban Heat Islands and Heat-Related Cardiovascular Morbidity Among Adults Aged 65+ in US Metropolitan Areas

BACKGROUND AND AIM. Extreme heat increases the risk of hospitalization due to cardiovascular disease (CVD). The United States (US) population largely resides in urban areas where climate change is projected to increase temperatures, yet little is known about this association across urban heat islands (UHIs). We aimed to identify the urban populations most at risk of and burdened by heat-related CVD morbidity. METHODS. We obtained daily counts of CVD hospital admissions (HAs) for Medicare enrollees (aged 65+) in 120 metropolitan areas (MSAs) in the contiguous US between 2000-2017. Daily average temperatures were estimated through the interpolation of monitor observations. A measure of UHI intensity was estimated from satellite-derived temperatures in urban vs. non-urban areas. We used quasi-Poisson regression with distributed-lag, non-linear models to estimate MSA-specific associations and pooled these estimates with multivariate meta-analyses. Stratified analyses were performed by UHI intensity quartile. We also calculated the number of CVD HAs attributable to heat in each MSA. RESULTS. Overall, extreme heat (99th percentile, ~28.6°C) was associated with a 3.0% [1.4%, 4.6%] increase in CVD HA risk relative to the minimum hospitalization temperature (MHT) (91st percentile, ~25.4°C). MSA-specific risks showed substantial differences, with higher risk in MSAs with lower annual average temperatures. We estimate that 1.6% (31,498) of CVD HAs on days above the MHT were attributable to heat. Although the interquartile risk differences were not significant, the highest quartile of UHI intensity was responsible for 47% (14,636) of all heat-attributable CVD HAs. CONCLUSIONS. Our results show that extreme heat increases the risk of CVD HAs among older adults in US urban areas, with considerable variation between cities. Areas with higher UHI intensity had the highest heat-related burden, indicating a potentially vulnerable subset of the urban population. This abstract does not necessarily reflect EPA policy. KEYWORDS. Extreme heat, cardiovascular morbidity, urban heat islands

Evaluation of multi-satellite precipitation products in estimating precipitation extremes over mainland China at annual, seasonal and monthly scales

The wide and consistent global coverage of satellite-based quantitative precipitation estimates (QPEs) has shown great potential for monitoring precipitation (PR) at large spatial scales. Evaluation of QPEs in estimating PR extremes is vital to forecasting hydrologic extremes. Here, we present a systematic evaluation of four commonly used QPEs: (1) the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), (2) Tropical Rainfall Measuring Mission 3B42 Version 7 (TRMM 3B42 V7), (3) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and (4) Multi-Source Weighted-Ensemble Precipitation (MSWEP), in their abilities to detect PR extremes in mainland China at annual-seasonal-monthly scales. Four Standard Extreme Precipitation Indices (SEPIs) are chosen as the assessment metrics, including the maximum 1-day PR (Rx1day), the simple PR intensity index (SDII), the count of days with PR ≥ 20 mm (R20mm), and the consecutive dry days (CDD). Results indicate that PERSIANN-CDR performs best for all SEPIs, followed by CHIRPS and TRMM 3B42 V7. All QPEs (except MSWEP) perform better (worse) in capturing CDD (SDII) than other SEPIs at all three timescales. However, large differences among the performance of QPEs in estimated seasonal SEPIs are found - CHIRPS (PERSIANN-CDR) outperforms the other QPEs in spring (summer and autumn), while PERSIANN-CDR and CHIRPS outperform the other QPEs in winter. All QPEs perform better in detecting extreme PR occurrence in summer than in other seasons, and spatially most of them perform better in humid southeastern China than in arid northwestern China. CHIRPS and TRMM 3B42 V7 overestimate Rx1day, R20mm and SDII in most of China, while MSWEP notably underestimates CDD in most of China and overestimates Rx1day, R20mm and SDII in western China.

Associations and burdens of relative humidity with cause-specific mortality in three Chinese cities.

This study aimed to investigate the association between relative humidity (RH) and various cause of mortality, and then quantify the RH-related mortality fraction of low and high RH under the assumption that causal effects exist. Daily cause-specific mortality counts from 2008 to 2011, and contemporaneous meteorological data in three Chinese cities were collected. Distributed lag nonlinear models were adopted to quantify the nonlinear and delayed effects of RH on mortality risk. Low and high RH were defined as RH lower or higher than the minimum mortality risk RH (MMRH), respectively. Corresponding RH-related mortality fractions were calculated in the explanatory analysis. From the three cities, 736,301 deaths were collected. RH (mean ± standard deviation) were 50.9 ± 20.0 for Beijing, 75.5 ± 8.6 for Chengdu, and 70.8 ± 14.6 for Nanjing. We found that low RH in Beijing and high RH (about 80-90%) in Chengdu was associated with increased all-cause mortality risk. Both low and high RH may increase the CVD mortality risk in Beijing. Both low and high (about 80-85%) RH may increase the COPD mortality risk in Chengdu. Low RH (about < 45%) was associated with increased diabetes mortality risk in Nanjing. Effects of extreme low and extreme high RH were delayed in these cities, except that extreme low effects on COPD mortality appeared immediately in Chengdu. The effects of extreme low RH are higher than that of the extreme high RH in Beijing and Nanjing, while contrary in Chengdu. Finally, under the causal effect assumption, 6.80% (95% eCI: 2.90, 10.73) all-cause mortality and 12.48% (95% eCI: 7.17, 16.80) CVD deaths in Beijing, 9.59% (95% eCI: 1.38, 16.88) COPD deaths in Chengdu, and 23.79% (95% eCI: 0.92, 387.93) diabetes mortality in Nanjing were attributable to RH. Our study provided insights into RH-mortality risk, helped draw relative intervention policies, and is also significant for future predictions of climate change effects under different scenarios.

Demographic Trends in Emergency Department Visits for Psychiatric Concerns During the COVID-19 Pandemic

ObjectiveTo describe changes in emergency department (ED) psychiatric visits during the pandemic in both rural and nonrural regions in the United States. MethodsThis cohort study was performed across 22 EDs in the Midwest and Southern United States from January 1, 2019 to April 22, 2021. Prevalence of psychiatric visits before and after the COVID-19 pandemic, defined as starting on March 1, 2020, were compared. Psychiatric and nonpsychiatric visits were defined on the basis of primary clinician–assigned diagnosis. The primary end point was average daily visits normalized to the average daily visit count before the pandemic, labeled as relative mean daily visits (RMDVs). Our study was deemed exempt by the Mayo Clinic IRB (#20-009350). We did not consent patients specifically for the study given that we only used retrospective data but adhered to the general consent for research used across all Mayo patients. ResultsPsychiatric visits decreased by 9% [RMDVs, 0.91; 95% confidence interval (CI), 0.89-0.93] during the pandemic period, whereas nonpsychiatric visits decreased by 17% (RMDVs, 0.83; 95% CI, 0.81-0.84). Black patients were the only demographic group with a significant increase in psychiatric visits during the pandemic (RMDVs, 1.12; 95% CI, 1.04-1.19). Periods of outbreaks of psychiatric emergencies were identified in most demographic groups, including among male and pediatric patients. However, the outbreaks detected among Black patients sustained the longest at 6 months. Unlike older adults who experienced outbreaks in the spring and fall of 2020, outbreaks among pediatric patients were detected later in 2021. ConclusionIn this multisite study, total ED visits declined during the pandemic; however, psychiatric visits declined less than nonpsychiatric visits. Black patients experienced a greater increase in psychiatric emergencies than other demographic groups. There is also a concern for increasing outbreaks of pediatric psychiatric visits as the pandemic progresses.

Associations of inclement weather and poor air quality with non-motorized trail volumes

Inclement weather and poor air quality present unfavorable conditions for active transportation. This study investigated associations of area-wide air pollution and inclement weather with non-motorized travel at two trail locations in northern Utah (one recreational, one utilitarian). Rainfall, snowfall, high/low temperatures, and high wind speed were measures of inclement weather, and overall air quality index (AQI) measured air pollution. This study fit time-series (ARIMA) regression models for the utilitarian and recreational sites (separately), using multiple years of daily non-motorized counts. Non-motorized travel was reduced significantly during inclement weather, and the effects of rainfall and cold temperatures were smaller for the utilitarian site than for the recreational site. Counts at the recreational site were higher on holidays, weekends, and days with greater snow depth. Although non-motorized counts were lower on days with worse air quality at the utilitarian location, they were higher at the recreational location. Results are interpreted in terms of the discretionary nature of recreational travel, particulars of the location and elevation of the recreational site, and a desire to escape pollution through outdoor recreation in a natural area.

The Impact of Anti-COVID-19 Measures on Mexico City Criminal Reports

ABSTRACT From the start of the COVID-19 outbreak, government measures impacted citizens’ behavior, particularly regarding social distancing and confinement. Whether or not these measures influenced criminal behavior is an area of particular interest. Findings, mainly concerned with the routine activity theory, have correlated restrictions on movement and circulation with a general decrease in crime. In this analysis, we use the case of Mexico City to estimate the impact of the national health crisis, and the corresponding government measures implemented, as well as their subsequent relaxation, on the daily crime count for six types of crimes (assault, burglary -residential and commercial-, domestic violence, larceny, robbery, and vehicle theft). We use generalized autoregressive conditional heteroscedasticity (GARCH) models to control for the volatility of the time series. While there is a growing body of literature that focuses on the study of criminal behavior during the pandemic, there is a scarcity of work that uses time series to analyze the impact of government measures and their consequences on criminal activity. Our results show a significant reduction in criminal reports for the analyzed crimes during the period of strictest social distancing measures, followed by an increase as these were gradually lifted or lightened.

Decadal Trends in the Migration Phenology of Diadromous Fishes Native to the Burrishoole Catchment, Ireland

Migration is an important ecological trait that allows animals to exploit resources in different habitats, obtaining extra energy for growth and reproduction. The phenology (or timing) of migration is a highly heritable trait, but is also controlled by environmental factors. Numerous studies have reported the advancement of species life-events with climate change, but the rate and significance of such advancement is likely to be species specific, spatially variable and dependent on interactions with population and ecosystem changes. This is particularly true for diadromous fishes which are sentinels of change in both freshwater and marine domains, and are subject to considerable multiple stressors including overfishing and habitat degradation. Here, we describe trends in the migration phenology of three native Irish migratory fishes over half a century, Atlantic salmon (Salmo salar), brown trout (Salmo trutta) and European eel (Anguilla anguilla). The trends were derived from daily counts of 745,263 fish moving upstream and downstream through the fish traps of the Burrishoole catchment, an internationally important monitoring infrastructure allowing a full census of migrating fish. We found that the start of the seaward migration of eel has advanced by one month since 1970. The commencement of the salmon smolt migration has advanced by one week, although the rest of the migration, and the entirety of the trout smolt run has remained stable. The beginning of the upstream migration of trout to freshwater has advanced by 20 days, while the end of the run is more than one month later than in the 1970’s. The greatest phenological shift has been in the upstream migration of adult salmon, with at least half of migrating fish returning between one and two months earlier from the marine environment compared to the 1970’s. The earlier return of these salmon is coincident with reduced marine survival and decreasing body size, indicating considerable oceanic challenges for this species. Our results demonstrate that the impacts of climate change on the phenology of diadromous fish are context-dependent and may interact with other factors. The mobilization of long-term datasets are crucial to parse the ecological impacts of climate change from other anthropogenic stresses.

COVID-19 restrictions, pub closures, and crime in Oslo, Norway

ABSTRACT Alcohol consumption and crime are closely linked and there is often more crime near pubs and bars. Few studies have considered the impact of restricting access to pubs or bars on crime, and the present study aims to provide more insight into this by using the restrictions to combat the COVID-19 pandemic as a natural experiment. In Oslo, Norway, alcohol serving was banned twice during 2020, and at other times during the year, restrictions were placed on how late it could be served. In the present paper, these restrictions are analysed, alongside more general COVID-19 restrictions, to assess their association with crime. To identify these, we employ negative binomial regression models of daily crime counts for nine types of crime adjusted for the day of the week, the week of the year, and the year itself. This is in addition to the presence, or absence, of alcohol-related restrictions and more general COVID-19 restrictions. The findings suggest that both, general restrictions and bans on serving alcohol, reduced crime, although not universally across all crime types and times of the day. When pubs are ordered not to sell alcohol after midnight there appears to be an unexpected increase in crime.

Clinical profile of atypical manifestations of dengue fever in children

Objectives: The objective of the study is to study the clinical profile and outcome of atypical manifestations of dengue fever in children. Methods: A case series study design was conducted in S.Nijalingappa Medical College &amp; H.S.K Hospital, Bagalkot. A detailed history was compiled, as well as the current complaints. The study subjects clinical progress was tracked until they were discharged. In all of the cases, basic tests such as a full Haemogram, Dengue serology and Daily Platelet count and Hematocrit were performed. Other tests such as LFT, USG Abdomen, Chest X-ray, ECG, 2D-ECHO and MRI brain are performed as needed in cases of Severe Dengue / Atypical symptoms. Results: The study covered 100 instances, with males accounting for 52 percent and females for 48 percent. Dengue fever, dengue fever without warning signs, and severe dengue were found in 29 percent, 43 percent, and 28 percent of the cases, respectively, in this study. Atypical signs were seen in more than half of the cases (59%) out of 100. We had 8 cases of severe dengue with SGPT/SGOT above 1000 IU in our study and two of them had Fulminant Hepatic Failure with the highest SGPT value of 6500 IU.

Autoregressive count data modeling on mobility patterns to predict cases of COVID-19 infection

At the beginning of 2022 the global daily count of new cases of COVID-19 exceeded 3.2 million, a tripling of the historical peak value reported between the initial outbreak of the pandemic and the end of 2021. Aerosol transmission through interpersonal contact is the main cause of the disease’s spread, although control measures have been put in place to reduce contact opportunities. Mobility pattern is a basic mechanism for understanding how people gather at a location and how long they stay there. Due to the inherent dependencies in disease transmission, models for associating mobility data with confirmed cases need to be individually designed for different regions and time periods. In this paper, we propose an autoregressive count data model under the framework of a generalized linear model to illustrate a process of model specification and selection. By evaluating a 14-day-ahead prediction from Sweden, the results showed that for a dense population region, using mobility data with a lag of 8 days is the most reliable way of predicting the number of confirmed cases in relative numbers at a high coverage rate. It is sufficient for both of the autoregressive terms, studied variable and conditional expectation, to take one day back. For sparsely populated regions, a lag of 10 days produced the lowest error in absolute value for the predictions, where weekly periodicity on the studied variable is recommended for use. Interventions were further included to identify the most relevant mobility categories. Statistical features were also presented to verify the model assumptions.

Schools under mandatory testing can mitigate the spread of SARS-CoV-2

We use event study models based on staggered summer vacations in Germany to estimate the effect of school reopenings after the summer of 2021 on the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Estimations are based on daily counts of confirmed coronavirus infections across all 401 German counties. A central antipandemic measure in German schools included mandatory rapid testing multiple times per week. Our results are consistent with mandatory testing contributing to the containment of the viral spread. We find a short-term increase in infection rates right after summer breaks, indicating the uncovering of otherwise undetected (asymptomatic) cases through the testing. After a period of about 2 wk after school reopenings, the growth of case numbers is smaller in states that reopened schools compared with the control group of states still in summer break. The results show a similar pattern for older age groups as well, arguably as a result of detected clusters through the school testing. This means that under certain conditions, open schools can play a role in containing the spread of the virus. Our results suggest that closing schools as a means to reduce infections may have unintended consequences by giving up surveillance and should be considered only as a last resort.

Spatiotemporal Changes in Mean and Extreme Climate: Farmers’ Perception and Its Agricultural Implications in Awash River Basin, Ethiopia

The increase in the intensity and frequency of climate extremes threatens socioeconomic development. This study examines variability of mean and extreme climate, farmers’ perception of the changes, and impacts in the Awash River Basin. Daily rainfall and temperature data were used to analyze 23 extreme climate indices. The Mann–Kendall test was used to assess the magnitude and significance of the changes. Results show an increase in minimum (0.019–0.055 °C/year) and maximum temperatures (0.049–0.09 °C/year), while total rainfall is on a downward trend (from −3.84 mm/year to −10.26 mm/year). Warm extreme temperature indicators, including warmest day (TXx), warmest night (TNx), warm day (TX90p), warm night (TN90p), and warm spell duration indicator (WSDI), show a significant increasing trend (p &lt; 0.05). Nevertheless, except the tepid–cool humid agroecology zone, cold extreme temperature indicators in cool days (TN10p), cool nights (TX10p), and cold spell duration (CSDI) are declining. Extreme precipitation indices, including maximum 1-day precipitation amount (RX1day), count of days when precipitation ≥10 mm (R10 mm), maximum 5-day precipitation amount (RX5day), count of days when precipitation ≥20 mm (R20mm), very wet days (R95p), extreme wet days (R99p), and total precipitation (PRCPTOT), show a decreasing trend. The perception of most farmers’ on climate change and climate extremes agreed with climate records. The major impacts perceived and asserted over all agroecologies are food price inflation, crop productivity decline, crop pests and diseases spread, livestock disease increase, and the emergence of pests and weeds. The increasing trend in extreme warm temperatures, decreasing trend in the cold extreme, and declining trend in precipitation indicators affected agricultural productivity and farmers whose livelihood depends on rainfed agriculture. This agroecology-specific study provides critical information to policymakers, decision makers, and farmers about the potential impacts of climate change and extreme events, leading to the development of agroecology-based adaptation measures.