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Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"
<p><strong>Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"</strong></p> <p><em>cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".</em></p> <p>These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".</p> <p><strong>40-lifetables.csv</strong></p> <p>Life table statistics 2015 through 2021 by sex, region and quarter with uncertainty quantiles based on Poisson replication of death counts. Actual life tables and expected life tables (under the assumption of pre-COVID mortality trend continuation) are provided.</p> <p><strong>30-lt_input.csv</strong></p> <p>Life table input data.</p> <ul> <li>`id`: unique row identifier</li> <li>`region_iso`: iso3166-2 region codes</li> <li>`sex`: Male, Female, Total</li> <li>`year`: iso year</li> <li>`age_start`: start of age group</li> <li>`age_width`: width of age group, Inf for age_start 100, otherwise 1</li> <li>`nweeks_year`: number of weeks in that year, 52 or 53</li> <li>`death_total`: number of deaths by any cause</li> <li>`population_py`: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)</li> <li>`death_total_nweeksmiss`: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)</li> <li>`death_total_minnageraw`: the minimum number of age-groups in the raw input data within this region-sex-year stratum</li> <li>`death_total_maxnageraw`: the maximum number of age-groups in the raw input data within this region-sex-year stratum</li> <li>`death_total_minopenageraw`: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum</li> <li>`death_total_maxopenageraw`: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum</li> <li>`death_total_source`: source of the all-cause death data</li> <li> <p>`death_total_prop_q1`: observed proportion of deaths in first quarter of year</p> </li> <li> <p>`death_total_prop_q2`: observed proportion of deaths in second quarter of year</p> </li> <li> <p>`death_total_prop_q3`: observed proportion of deaths in third quarter of year</p> </li> <li> <p>`death_total_prop_q4`: observed proportion of deaths in fourth quarter of year</p> </li> <li> <p>`death_expected_prop_q1`: expected proportion of deaths in first quarter of year</p> </li> <li> <p>`death_expected_prop_q2`: expected proportion of deaths in second quarter of year</p> </li> <li> <p>`death_expected_prop_q3`: expected proportion of deaths in third quarter of year</p> </li> <li> <p>`death_expected_prop_q4`: expected proportion of deaths in fourth quarter of year</p> </li> <li>`population_midyear`: midyear population (July 1st)</li> <li>`population_source`: source of the population count/exposure data</li> <li>`death_covid`: number of deaths due to covid</li> <li>`death_covid_date`: number of deaths due to covid as of <date></li> <li>`death_covid_nageraw`: the number of age groups in the covid input data</li> <li>`ex_wpp_estimate`: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year</li> <li>`ex_hmd_estimate`: life expectancy estimates from the Human Mortality Database</li> <li>`nmx_hmd_estimate`: death rate estimates from the Human Mortality Database</li> <li>`nmx_cntfc`: Lee-Carter death rate projections based on trend in the years 2015 through 2019</li> </ul> <p><em>Deaths</em></p> <ul> <li>source: <ul> <li>STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)</li> <li>ONS for GB-EAW pre 2020</li> <li>CDC for US pre 2020</li> </ul> </li> <li>STMF: <ul> <li>harmonized to single ages via pclm</li> <li>pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110</li> <li>smoothing parameters estimated via BIC grid search seperately for every pclm iteration</li> <li>last age group set to [110,111)</li> <li>ages 100:110+ are then summed into 100+ to be consistent with mid-year population information</li> <li>deaths in unknown weeks are considered; deaths in unknown ages are not considered</li> </ul> </li> <li>ONS: <ul> <li>data already in single ages</li> <li>ages 100:105+ are summed into 100+ to be consistent with mid-year population information</li> <li>PCLM smoothing applied to for consistency reasons</li> </ul> </li> <li>CDC: <ul> <li>The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data</li> </ul> </li> </ul> <p><em>Population</em></p> <ul> <li>source: <ul> <li>for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019</li> <li>for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100</li> </ul> </li> <li>mid-year population <ul> <li>mid-year population translated into exposures: <ul> <li>if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates</li> <li>if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364\*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.</li> </ul> </li> </ul> </li> </ul> <p><em>COVID deaths</em></p> <ul> <li>source: COVerAGE-DB (https://osf.io/mpwjq/)</li> <li>the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total</li> </ul> <p><em>External life expectancy estimates</em></p> <ul> <li>source: <ul> <li>World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019</li> <li>Human Mortality Database (https://mortality.org/), single year and age tables</li> </ul> </li> </ul>
Data for Figures and Tables in "Bounce backs amid continued losses: Life expectancy changes since COVID-19"
<p><strong>Data for Figures and Tables in "Bounce backs amid continued losses: Life expectancy changes since COVID-19"</strong></p> <p><em>cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".</em></p> <p>These are CSV files of data in the figures and tables published in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".</p> <p><strong>50-e0diffT.csv</strong></p> <p>Figure 1: Life expectancy changes 2019/20 and 2020/21 across countries. The countries are ordered by increasing cumulative life expectancy losses since 2019. Grey dots indicate the average annual LE changes over the years 2015 through 2019.</p> <p><strong>51-arriagaT.csv</strong></p> <p>Figure 2: Age contributions to life expectancy changes since 2019 separated for 2020 and 2021. The position of the arrowhead indicates the total contribution of mortality changes in a given age group to the change in life expectancy at birth since 2019. The discontinuity in the arrow indicates those contributions separately for the years 2020 and 2021. Annual contributions can compound or reverse. The total life expectancy change from 2019 to 2021 in a given country is the sum of the arrowhead positions across age.</p> <p><strong>52-sexdiff.csv</strong></p> <p>Figure 3: Change in the female life expectancy advantage from 2019 through 2021. Blue colors indicate an increase and red colors a decrease in the female life expectancy advantage. Muted colors indicate non-significant changes.</p> <p><strong>53-e0diffcodT.csv</strong></p> <p>Figure 4: Life expectancy deficit in 2021 decomposed into contributions by age and cause of death. LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.</p> <p><strong>55-vaxe0.csv</strong></p> <p>Figure 5: Years of life expectancy deficit during October through December 2021 contributed by ages <60 and 60+ against % of population twice vaccinated by October 1st in the respective age groups. LE deficit is defined as the counterfactual LE from a Lee-Carter mortality forecast based on death rates for the fourth quarter of the years 2015 to 2019 minus observed LE.</p> <p><strong>54-tab_arriaga.csv</strong></p> <p>Table 1: Months of life expectancy (LE) changes and deficits (labelled ES) since the start of the pandemic attributed to age-specific mortality changes (labelled AT). LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.</p>
Figure 2 in Life table parameters of Tetranychus urticae (Trombidiformes: Tetranychidae) on four strawberry cultivars
Figure 2. Age-specific survival rate (lx), age-stage fecundity of female (fxj) and age-specific fecundity rate (mx) of Tetranychus urticae on four strawberry cultivars.
Figure 4 in Life table parameters of Tetranychus urticae (Trombidiformes: Tetranychidae) on four strawberry cultivars
Figure 4. Age-specific survivorship (lx), and fecundity (mx) of Tetranychus urticae on four strawberry cultivars.
Figure 1 in Biology and life-table of Typhlodromus (Anthoseius) athenas (Acari: Phytoseiidae) fed with the Old World Date Mite, Oligonychus afrasiaticus (Acari: Tetranychidae)
Figure 1 Population dynamics ofO. afrasiaticus andT. (A.) athenas on date of 'Alig' cultivar at Segdoud, South of Tunisia in 2005 and 2006.
Neolithic life tables de 2024.02
<p>Data from the literature containing information on the age at death of Neolithic burials from Germany. The data were taken from mortality tables (Dx), individual data or bar charts. The data set does not claim to be complete, but focuses on larger burial groups.</p>
Data and code for: Nonlinear life table response analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers
<p>Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. In this study, we compare the relative efficacy of linear and second-order LTRE analyses in capturing changes in population growth rate caused by environmental driver changes. To explore this question, we analyze demographic data collected for three long-lived plant species: <em>Ardisia escallonioides</em> (Pascarella & Horvitz, 1998), <em>Silene acaulis</em>, and <em>Bistorta vivipara</em> (Doak & Morris, 2010). This repository includes data files containing vital rate (survival, growth, reproduction) observations or models for our three case studies, as well as an R script in which we use these demographic data to calculate linear and second-order LTRE approximations of changes in population growth rate for each system and generate the figures we present in our paper.</p>
Figure 2 in Development and life table parameters of the Phytoseius corniger Wainstein (Acari: Phytoseiidae) feeding on the two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae) under laboratory conditions
Figure 2. The age-specific survival rate (lx), and fecundity (mx) of Phytoseius corniger fed on Tetranychus urticae under laboratory conditions (25 ± 2 °C, 55 ± 5% of RH, and 16L: 8D h photoperiod).
Figure 1 in Development and life table parameters of the Phytoseius corniger Wainstein (Acari: Phytoseiidae) feeding on the two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae) under laboratory conditions
Figure 1. Age-stage specific survival rate (sjx) of the parent cohort of bisexual Phytoseius corniger fed on Tetranychus urticae under laboratory conditions (25 ± 2 °C, 55 ± 5% of RH, and 16L: 8D h photoperiod). Note: L stands for larva, N1 for protonymph, and N2 for deutonymph, respectively.
Figure 1 in Influence of temperature and prey type on life-table parameters and consumption rate of Stethorus gilvifrons (Mulsant) (Coleoptera: Coccinellidae) on three tetranychid mites
Figure 1. Age-stage-specific survival rate (lx) and age-specific fecundity (mx) curves of Stethorus gilvifrons on different prey types and different temperatures.
Life tables and graphs for Bahry (2022) - Equilibrium conditions in the evolution of senescence [MSc thesis, Carleton Univeristy]
<p>Life table data, and derived quantities, for <em>Equilibrium Conditions in the Evolution of Senescence</em> (Bahry, 2022, MSc thesis); adapted from the supplementary data of (Jones et al., 2014). Life table data for human (Japan 2009), human (Aché hunter-gatherer), fruit fly, Soay sheep, freshwater hydra, and desert tortoise.</p> <p>Basic life table quantities: age interval <span class="math-tex">\((X)\)</span>; survival function <span class="math-tex">\((l_X)\)</span>; and age-specific interval fecundity <span class="math-tex">\((m_X)\)</span>. Derived quantities include interval average force of mortality; reproductive value; residual reproductive value; Hamilton's indicators of the age-specific forces of selection; and actual age-specific mortality vs. predicted age-specific mortality based on models treated in (Bahry, 2022).</p> <p>In the original life tables of Jones et al. (2014), desert tortoises negatively senesce over the range of observed ages, but had a final observed cut-off age of 74; this causes reproductive value to artifactually fall to 0 as age-approached the cutoff. To get around this, I also used an extrapolated desert tortoise life table, assuming the age-74 mortality and fecundity rates remained constant until age 1000, then using the extrapolated life table to calculate reproductive value (and Hamilton's indicators) up to the cutoff age 74.</p> <p><strong>References</strong></p> <p>Bahry, D. (2022). <em>Equilibrium Conditions in the Evolution of Senescence</em> [Master's thesis, Carleton University].</p> <p>Jones, O. R. et al. (2014). Diversity of ageing across the tree of life. <em>Nature</em> 505: 169–174. https://doi.org/10.1038/nature12789</p>
Figure 1 in Biology and life table parameters of Proprioseiopsis lindquisti on three eriophyid mites (Acari: Phytoseiidae: Eriophyidae)
Figure 1. Age-specific survival rate (lx), age-stage specific fecundity of female (fxj) and age-specific fecundity rate (mx) of Propriopseiosis lindquisti on three eriophyid mites.
Fig. 1 in The life table parameters of Megalurothrips usitatus (Thysanoptera: Thripidae) on four leguminous crops
Fig. 1. Mean (± SE) survival rate of Megalurothrips usitatus on 4 leguminous crops. Means values with same letter are not significantly different by Tukey's multiple range test (P <0.05).
Urban-rural life tables for Scotland, 1861-1910
<p>This data set contains the life tables the were computed for the study presented in: Torres, C., V. Canudas-Romo, and J. Oeppen (2019) 'The contribution of urbanization to changes in life expectancy in Scotland, 1861–1910', <em>Population Studies</em>, 73:3, 387-404, DOI: 10.1080/00324728.2018.1549746</p> <p>The life tables are by sex and urban-rural category. For reasons explained in the paper, the tables cover periods of different lengths, from 1861 to 1910.</p> <p><strong>Example of how to load the data in R:</strong></p> <p>LT <- read.table("Urban-Rural-LifeTables-Scotland-1861-1910.txt", header = T, sep = ";")</p> <p><strong>Description of each column:</strong><br> Period: time-interval, including the first and excluding the last indicated years (e.g., [1861,1866) corresponds to the years from 1861 to 1865). Available periods: 1861-1865, 1866-1870, 1871-1874, 1875-1877, 1878-1880, 1881-1885, 1886-1890, 1891-1892, 1893-1896, 1897-1900, 1901-1905, 1906-1910.<br> Population: Rural, Semi-Urban, Urban, or Total population (see definitions in Torres et al. 2019)<br> Sex: Female or Male<br> x : Age (from 0 to 110+, by single ages)<br> nmx: Death rate in the age interval [x, x+n)<br> nax: average number of person-years lived in the age interval [x, x+n) by those who die in that interval<br> nqx: Probability of dying in the age interval [x, x+n)<br> lx: number of survivors at exact age x, or probability of surviving until exact age x<br> ndx: Life-table deaths in the age interval [x, x+n)<br> nLx: Person-years lived in the age interval [x, x+n)<br> Tx: Person-years lived above age x<br> ex: Remaining life expectancy at age x</p> <p>For more information about life tables in general, see: Preston, S., Heuveline, P., and Guillot, M. (2001). <em>Demography: Measuring and Modeling Population Processes</em>. Wiley-Blackwell</p>
Figure 3 in Morphology of immature stages, biological parameters and life table of Microtechnites bractatus (Hemiptera: Miridae) on different host plants
Figure 3 Average survival of Microtechnites bractatus nymphs fed with alfalfa, white clover, potato, wheat, and beans under laboratory conditions (25 ± 2°C, photoperiod 12L:12D). *Lines followed by different letters differ from each other by the paired Mentex-Cox test (Log Rank) (df=1, p<0.05).
Figure 2 in Morphology of immature stages, biological parameters and life table of Microtechnites bractatus (Hemiptera: Miridae) on different host plants
Figure 2 Five nymphal instars of Microtechnites bractatus: (A) first instar; (B) second instar; (C) third instar; (D) fourth instar; (E) fifth instar reduced wing pads for adult brachypterous (female); (F) elongated fifth-instar wing pads for adult macropterous (male).
Figure 1 in Morphology of immature stages, biological parameters and life table of Microtechnites bractatus (Hemiptera: Miridae) on different host plants
Figure 1 Eggs of Microtechnites bractatus oviposited on bean plants,Phaseolus vulgaris L. (A) egg recently oviposited and removed from the plant; (B) seven-day-old egg removed from the plant; (C) newly oviposited eggs; (D) eggs after seven days of oviposition.
Fig. 2 in Biology and fertility life table of Bactrocera carambolae on grape and acerola
Fig. 2. Survival curves of Bactrocera carambolae adults grown on grapes (Vitis vinifera) and acerola (Malpighia emarginata) in laboratory (26 ± 2 ◦C; 60 ± 10% RH; photophase 12 h).
Fig. 2 in Effect of different diets on biology, reproductive variables and life and fertility tables of Harmonia axyridis (Pallas) (Coleoptera, Coccinellidae)
Fig. 2. Survival probability (lx), expressed in percentage, and specific fertility (mx) expressed as average number of eggs per day of Harmonia axyridis (Pallas, 1773) fed on Brevicoryne brassicae Linnaeus, 1758. Temperature 25 ± 1 ◦C, 70 ± 10% RU and humidity and 12:12 h L:D.
Fig. 1 in Effect of different diets on biology, reproductive variables and life and fertility tables of Harmonia axyridis (Pallas) (Coleoptera, Coccinellidae)
Fig. 1. Survival probability (lx), expressed in percentage, and specific fertility (mx) expressed as average number of eggs per day of Harmonia axyridis (Pallas, 1773) fed on Cinara atlantica (Wilson, 1919). Temperature 25 ± 1 ◦C, 70 ± 10% RU and humidity and 12:12 h L:D.
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