Anti-clustering in the national SARS-CoV-2 daily infection counts

The noise in daily infection counts of an epidemic should be super-Poissonian due to intrinsic epidemiological and administrative clustering. Here, we use this clustering to classify the official national SARS-CoV-2 daily infection counts and check for infection counts that are unusually anti-clustered. We adopt a one-parameter model of $\phi _i^{\prime}$ infections per cluster, dividing any daily count ni into $n_i/ _i^{\prime}$ ‘clusters’, for ‘country’ i. We assume that ${n_i}/\phi _i^{\prime}$ on a given day j is drawn from a Poisson distribution whose mean is robustly estimated from the four neighbouring days, and calculate the inferred Poisson probability $P_{ij}^{\prime}$ of the observation. The $P_{ij}^{\prime}$ values should be uniformly distributed. We find the value $\phi_i$ that minimises the Kolmogorov–Smirnov distance from a uniform distribution. We investigate the (ϕi, Ni) distribution, for total infection count Ni. We consider consecutive count sequences above a threshold of 50 daily infections. We find that most of the daily infection count sequences are inconsistent with a Poissonian model. Most are found to be consistent with the ϕi model. The 28-, 14- and 7-day least noisy sequences for several countries are best modelled as sub-Poissonian, suggesting a distinct epidemiological family. The 28-day least noisy sequence of Algeria has a preferred model that is strongly sub-Poissonian, with $\phi _i^{28} < 0.1$. Tajikistan, Turkey, Russia, Belarus, Albania, United Arab Emirates and Nicaragua have preferred models that are also sub-Poissonian, with $\phi _i^{28} < 0.5$. A statistically significant (Pτ < 0.05) correlation was found between the lack of media freedom in a country, as represented by a high Reporters sans frontieres Press Freedom Index (PFI2020), and the lack of statistical noise in the country’s daily counts. The ϕi model appears to be an effective detector of suspiciously low statistical noise in the national SARS-CoV-2 daily infection counts.

Environmental factors and asthma hospitalization in Montreal, Canada, during spring 2006–2008: a synergy perspective

The aim of this study is to analyze the synergy between environmental factors (pollutant, allergenic birch pollen, weather) and its relationship with asthma hospitalization in Montreal, Canada. The data is stratified into weather types and the study restricted to spring season to limit the impact of multiple confounders. Results shows that the daily count of asthma hospitalization (spring 2006–2008) in situation of warm fronts or trowals (daily average of 3.78 counts, CI 95% 2.95–4.61) was much higher (p < 0.001) than in other situations (2.49 counts, CI 95% 2.37–2.71). Moreover, the explained variance of asthma hospitalization due to air pollution rises from about less than 7% (in the case of no stratification) to about 28% (R = 0.53, p < 0.05 with stratification). Statistical tests for interaction and overall results point towards a synergy between environmental factors which exacerbates asthma. A new concept named frontal asthma is proposed to explain several results found here and in the open literature.

Trip patterns and revenue of shared e-scooters in Louisville, Kentucky

Data on shared e-scooters in Louisville, Kentucky are analyzed. The data includes check out times, trip duration, and trip distance. Patterns in usage are evaluated and suggest that e-scooters are probably not being used for commute trips, but potentially could be for short commutes. Daily weather data is linked to daily count data to analyze how average temperature, wind speed, precipitation and snow affects usage. Higher average temperatures are not associated with more trips but do lead to longer and faster trips. Rain and snow reduce usage while higher winds slightly reduce trip distances. An estimate of current revenue from the existing system is about $500/day.

An assessment of the Ambrosia L. pollen threat at a regional scale using the example of the town of Sosnowiec (Silesian Uplands, Poland)

The investigation of <i>Ambrosia</i> pollen counts in the air of Sosnowiec was carried out from 1998 to 2010 by means of the volumetric method. The pollen season which was determined by means of the 98% method started at the end of July and the beginning of August and lasted until the end of October. The highest <i>Ambrosia</i> pollen count was recorded in 1999 (222 grains x m^-3) and the lowest in 2001 (18 grains x m^-3). It was stated that the daily count of pollen grains depended on the wind direction and maximum air temperature. The strongest correlations were found with maximum temperature and with a wind direction from the south east. A high negative correlation coefficient was found between the frequency of inflows of air masses from the west and the annual total of pollen grains and the value of the maximum daily count. The closest sites of <i>Ambrosia</i> L. are at a distance of 25-40 kilometres from the sampling point. Significant correlations with the frequency of inflow of air masses can support the conclusion that <i>Ambrosia</i> pollen grains recorded in Sosnowiec were most probably carried not only from local sources but also, at least in part, from distant places.

Earthquake frequency and prediction

The coefficient p in n(t) = n1t−p, where n(t) is the daily count of earthquakes and n1 is the number of earthquakes on the first day following a larger earthquake, is ≦1 for foreshock sequences, ≳1 for double-main shock sequences, and »1 for aftershock sequences with a single largest earthquake. For p »1, the magnitude of the largest aftershock and the cutoff time of the aftershocks can be estimated. These observations are the basis for an earthquake prediction technique successfully used in the Peoples Republic of China (PRC).