Towards a theoretical determination of the geographical probability distribution of meteoroid impacts on Earth

Tunguska and Chelyabinsk impact events occurred inside a geographical area of only 3.4\% of the Earth's surface. Although two events hardly constitute a statistically significant demonstration of a geographical pattern of impacts, their spatial coincidence is at least tantalizing. To understand if this concurrence reflects an underlying geographical and/or temporal pattern, we must aim at predicting the spatio-temporal distribution of meteoroid impacts on Earth. For this purpose we designed, implemented and tested a novel numerical technique, the "Gravitational Ray Tracing" (GRT) designed to compute the relative impact probability (RIP) on the surface of any planet. GRT is inspired by the so-called ray-casting techniques used to render realistic images of complex 3D scenes. In this paper we describe the method and the results of testing it at the time of large impact events. Our findings suggest a non-trivial pattern of impact probabilities at any given time on Earth. Locations at $60-90\deg$ from the apex are more prone to impacts, especially at midnight. Counterintuitively, sites close to apex direction have the lowest RIP, while in the antapex RIP are slightly larger than average. We present here preliminary maps of RIP at the time of Tunguska and Chelyabinsk events and found no evidence of a spatial or temporal pattern, suggesting that their coincidence was fortuitous. We apply the GRT method to compute theoretical RIP at the location and time of 394 large fireballs. Although the predicted spatio-temporal impact distribution matches marginally the observed events, we successfully predict their impact speed distribution.Comment: 16 pages, 11 figures. Accepted for publication in MNRA

Assessing racial/ethnic and nativity disparities in US cancer mortality using a new integrated platform

Foreign-born (FB) populations in the US have significantly increased, yet cancer trends remain unexplored. Survey-based Population-Adjusted Rate Calculator (SPARC) is a new tool for evaluating nativity differences in cancer mortality. Using SPARC, we calculated 3-year (2016-2018) age-adjusted mortality rates (AAMRs) and rate ratios (RRs) for common cancers by sex, age group, race/ethnicity, and nativity. Trends by nativity were examined for the first time for 2006-2018. Traditional cancer statistics draw populations from decennial censuses. However, nativity-stratified populations are from the American Community Surveys, thus involve sampling errors. To rectify this, SPARC employed bias-corrected estimators. Death counts came from the National Vital Statistics System. AAMRs were higher among US-born (UB) populations across nearly all cancer types, with the largest UB- FB difference observed in lung cancer among Black females (RR = 3.67, 95%CI = 3.37-4.00). The well-documented White-Black differences in breast cancer mortality existed mainly among UB women. For all cancers combined, descending trends were more accelerated for the UB compared to the FB in all race/ethnicity groups with changes ranging from -2.6% per year in UB Black males to stable (non-significant) among FB Black females. Pancreas and liver cancers were exceptions with increasing, stable, or decreasing trends depending on nativity and race/ethnicity. Notably, FB Black males and FB Hispanic males did not show a favorable decline in colorectal cancer mortality. While all groups show beneficial cancer mortality trends, those with higher rates in 2006 have experienced sharper declines. Persistent disparities between the UB and the FB, especially among Black people, necessitate further investigation

Geographical, racial and socio-economic variation in life expectancy in the US and their impact on cancer relative survival - Fig 1

<p><b>Estimated and selected observed 2010 log mortality rates for males (A) and females (B) residing in the state of California by race and socio-economic status (SES). Observed log mortality rates are displayed for blacks and API in the high SES group (Q4-Q5).</b> White = Non-Hispanic (NH) White, Black = NH Black, API = NH Asian or Pacific Islander, AIAN = NH American Indian and American Natives, and Hisp. = Hispanics. For whites only, LT for the lowest (Q1) and highest (Q5) SES quintiles are shown. For blacks, Hispanics, and API we only estimated LT by 2 level SES: Low = Q1-Q3 SES and High = Q4-Q5 SES. Observed log mortality rates for blacks and for API’s are for the high SES group.</p

Life expectancy from birth to age 99 in 2010 by state and sex for whites and blacks, ordered by life expectancy for white males.

<p>The left and right end of the bars representing life expectancies estimates of patients living in counties with lowest and highest SES quintiles, respectively. The dots represent average life expectancy in the respective state, race and sex combination.</p

10-year expected survival for cancer patients diagnosed between 2000 and 2012 with any type of cancer by sex, race, age and geographic area calculated using the County SES-LT (black) versus the US-LT (gray).

<p>Registries are grouped from the highest SES (left of SEER-18) to the lowest SES (right of SEER-18).</p

Race state population estimates in 2010 and percent of population (all races combined) in each SES quintile.

<p>Race state population estimates in 2010 and percent of population (all races combined) in each SES quintile.</p

Trends in life expectancy from 1992 through 2012 for males and females by race and SES quintiles of their county of residency.

<p>Life expectancies are from birth to age 99 and the numbers in parentheses represent gains in life expectancy (in years) from 1992 to 2012.</p

10-year relative using US-LT and County SES-LT compared to 10-year cause specific survival for cancer patients diagnosed in the SEER-18 areas in 2000–2012 between ages 75 and 84 years both sexes combined.

<p>10-year relative using US-LT and County SES-LT compared to 10-year cause specific survival for cancer patients diagnosed in the SEER-18 areas in 2000–2012 between ages 75 and 84 years both sexes combined.</p

10-year relative survival using the County SES-LT (black) and the US-LT (gray), and 10-year cause-specific survival and its respective 95% confidence intervals (red) for patients diagnosed with any cancer between 2000 and 2012 by sex, age, and race.

<p>Registries are grouped from the highest SES (left of SEER-18) to the lowest SES (right of SEER-18).</p