Intuitionistc probability and the Bayesian objection to dogmatism

Given a few assumptions, the probability of a conjunction is raised, and the probability of its negation is lowered, by conditionalising upon one of the conjuncts. This simple result appears to bring Bayesian confirmation theory into tension with the prominent dogmatist view of perceptual justification – a tension often portrayed as a kind of ‘Bayesian objection’ to dogmatism. In a recent paper, David Jehle and Brian Weatherson observe that, while this crucial result holds within classical probability theory, it fails within intuitionistic probability theory. They conclude that the dogmatist who is willing to take intuitionistic logic seriously can make a convincing reply to the Bayesian objection. In this paper, I argue that this conclusion is premature – the Bayesian objection can survive the transition from classical to intuitionistic probability, albeit in a slightly altered form. I shall conclude with some general thoughts about what the Bayesian objection to dogmatism does and doesn’t show

Secondary organic aerosol formation from gasoline vehicle emissions in a new mobile environmental reaction chamber

We present a new mobile environmental reaction chamber for the simulation of the atmospheric aging of different emissions sources without limitation from the instruments or facilities available at any single site. Photochemistry is simulated using a set of 40 UV lights (total power 4 KW). Characterisation of the emission spectrum of these lights shows that atmospheric aging of emissions may be simulated over a range of temperatures (-7 to 25°C). A photolysis rate of NO2, JNO2, of (8.0±0.7)×10-3 s-1 was determined at 25°C. We demonstrate the utility of this new system by presenting results on the aging (OH=12×106 cm-3h) of emissions from a modern (Euro 5) gasoline car operated during a driving cycle (New European Driving Cycle, NEDC) on a chassis dynamometer in a vehicle test cell. Emissions from the entire NEDC were sampled and aged in the chamber. A thorough investigation of the composition of the gas phase emissions suggests that the observed SOA is from previously unconsidered precursors and processes. This large enhancement in PM mass from gasoline vehicle aerosol emissions due to SOA formation, if it occurs across a wider range of gasoline vehicles, would have significant implications for our understanding of the contribution of on-road gasoline vehicles to ambient aerosols.JRC.F.8-Sustainable Transpor

Two-stroke scooters are a dominant source of air pollution in many cities.

Fossil fuel-powered vehicles emit significant particulate matter, for example, black carbon and primary organic aerosol, and produce secondary organic aerosol. Here we quantify secondary organic aerosol production from two-stroke scooters. Cars and trucks, particularly diesel vehicles, are thought to be the main vehicular pollution sources. This needs re-thinking, as we show that elevated particulate matter levels can be a consequence of 'asymmetric pollution' from two-stroke scooters, vehicles that constitute a small fraction of the fleet, but can dominate urban vehicular pollution through organic aerosol and aromatic emission factors up to thousands of times higher than from other vehicle classes. Further, we demonstrate that oxidation processes producing secondary organic aerosol from vehicle exhaust also form potentially toxic 'reactive oxygen species'.This work was supported by the Swiss Federal Office for the Environment (FOEN), the Federal Roads Office (FEDRO), the Swiss National Science Foundation (Ambizione PZ00P2_131673, SAPMAV 200021_13016), the EU commission (FP7, COFUND: PSI-Fellow, grant agreement n.° 290605), the UK Natural Environment Research Council (NERC), the French Environment and Energy Management Agency (ADEME, Grant number 1162C00O2) and the Velux Foundation.This is the accepted manuscript version. The final version is available from http://www.nature.com/ncomms/2014/140513/ncomms4749/full/ncomms4749.html

Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data

Quantitative information on epidemiological quantities such as the incubation period and generation time of SARS-CoV-2 variants is scarce. We analyzed a dataset collected during contact tracing activities in the province of Reggio Emilia, Italy, throughout 2021. We determined the distributions of the incubation period for the Alpha and Delta variants using information on negative PCR tests and the date of last exposure from 282 symptomatic cases. We estimated the distributions of the intrinsic generation time using a Bayesian inference approach applied to 9724 SARS-CoV-2 cases clustered in 3545 households where at least one secondary case was recorded. We estimated a mean incubation period of 4.9 days (95% credible intervals, CrI, 4.4-5.4) for Alpha and 4.5 days (95%CrI 4.0-5.0) for Delta. The intrinsic generation time was estimated to have a mean of 7.12 days (95% CrI 6.27-8.44) for Alpha and of 6.52 days (95%CrI 5.54-8.43) for Delta. The household serial interval was 2.43 days (95%CrI 2.29-2.58) for Alpha and 2.74 days (95%CrI 2.62-2.88) for Delta, and the estimated proportion of pre-symptomatic transmission was 48-51% for both variants. These results indicate limited differences in the incubation period and intrinsic generation time of SARS-CoV-2 variants Alpha and Delta compared to ancestral lineages

SARS-CoV-2 transmission patterns in educational settings during the Alpha wave in Reggio-Emilia, Italy

: Different monitoring and control policies have been implemented in schools to minimize the spread of SARS-CoV-2. Transmission in schools has been hard to quantify due to the large proportion of asymptomatic carriers in young individuals. We applied a Bayesian approach to reconstruct the transmission chains between 284 SARS-CoV-2 infections ascertained during 87 school outbreak investigations conducted between March and April 2021 in Italy. Under the policy of reactive quarantines, we found that 42.5% (95%CrI: 29.5-54.3%) of infections among school attendees were caused by school contacts. The mean number of secondary cases infected at school by a positive individual during in-person education was estimated to be 0.33 (95%CrI: 0.23-0.43), with marked heterogeneity across individuals. Specifically, we estimated that only 26.0% (95%CrI: 17.6-34.1%) of students and school personnel who tested positive during in-person education caused at least one secondary infection at school. Positive individuals who attended school for at least 6 days before being isolated or quarantined infected on average 0.49 (95%CrI: 0.14-0.83) secondary cases. Our findings provide quantitative insights on the contribution of school transmission to the spread of SARS-CoV-2 in young individuals. Identifying positive cases within 5 days after exposure to their infector could reduce onward transmission at school by at least 30%

Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 to January 2022.

BackgroundThe SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021.AimTo comprehensively describe Omicron spread in Italy in the 2 subsequent months and its impact on the overall SARS-CoV-2 circulation at population level.MethodsWe analyse data from four genomic surveys conducted across the country between December 2021 and January 2022. Combining genomic sequencing results with epidemiological records collated by the National Integrated Surveillance System, the Omicron reproductive number and exponential growth rate are estimated, as well as SARS-CoV-2 transmissibility.ResultsOmicron became dominant in Italy less than 1 month after its first detection, representing on 3 January 76.9-80.2% of notified SARS-CoV-2 infections, with a doubling time of 2.7-3.3 days. As of 17 January 2022, Delta variant represented < 6% of cases. During the Omicron expansion in December 2021, the estimated mean net reproduction numbers respectively rose from 1.15 to a maximum of 1.83 for symptomatic cases and from 1.14 to 1.36 for hospitalised cases, while remaining relatively stable, between 0.93 and 1.21, for cases needing intensive care. Despite a reduction in relative proportion, Delta infections increased in absolute terms throughout December contributing to an increase in hospitalisations. A significant reproduction numbers' decline was found after mid-January, with average estimates dropping below 1 between 10 and 16 January 2022.ConclusionEstimates suggest a marked growth advantage of Omicron compared with Delta variant, but lower disease severity at population level possibly due to residual immunity against severe outcomes acquired from vaccination and prior infection

Evaluation of the 2022 West Nile virus forecasting challenge, USA

\ua9 2025. The Author(s). BACKGROUND: West Nile virus (WNV) is the most common cause of mosquito-borne disease in the continental USA, with an average of ~1200 severe, neuroinvasive cases reported annually from 2005 to 2021 (range 386-2873). Despite this burden, efforts to forecast WNV disease to inform public health measures to reduce disease incidence have had limited success. Here, we analyze forecasts submitted to the 2022 WNV Forecasting Challenge, a follow-up to the 2020 WNV Forecasting Challenge. METHODS: Forecasting teams submitted probabilistic forecasts of annual West Nile virus neuroinvasive disease (WNND) cases for each county in the continental USA for the 2022 WNV season. We assessed the skill of team-specific forecasts, baseline forecasts, and an ensemble created from team-specific forecasts. We then characterized the impact of model characteristics and county-specific contextual factors (e.g., population) on forecast skill. RESULTS: Ensemble forecasts for 2022 anticipated a season at or below median long-term WNND incidence for nearly all (> 99%) counties. More counties reported higher case numbers than anticipated by the ensemble forecast median, but national caseload (826) was well below the 10-year median (1386). Forecast skill was highest for the ensemble forecast, though the historical negative binomial baseline model and several team-submitted forecasts had similar forecast skill. Forecasts utilizing regression-based frameworks tended to have more skill than those that did not and models using climate, mosquito surveillance, demographic, or avian data had less skill than those that did not, potentially due to overfitting. County-contextual analysis showed strong relationships with the number of years that WNND had been reported and permutation entropy (historical variability). Evaluations based on weighted interval score and logarithmic scoring metrics produced similar results. CONCLUSIONS: The relative success of the ensemble forecast, the best forecast for 2022, suggests potential gains in community ability to forecast WNV, an improvement from the 2020 Challenge. Similar to the previous challenge, however, our results indicate that skill was still limited with general underprediction despite a relative low incidence year. Potential opportunities for improvement include refining mechanistic approaches, integrating additional data sources, and considering different approaches for areas with and without previous cases