Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Monte Carlo Determination of Dosimetric Parameters of a New I-125 Brachytherapy Source According to AAPM TG-43 (U1) Protocol

Background: I-125 is one of the important sources frequently used in brachytherapy. Up to now, several different commercial models of this source type have been introduced to the clinical radiation oncology applications. Recently, a new source model, IrSeed-125, has been added to this list. The aim of the present study is to determine the dosimetric parameters of this new source model based on the recommendations of TG-43 (U1) protocol using Monte Carlo simulation. Methods: The dosimetric characteristics of Ir-125 including dose rate constant, radial dose function, 2D anisotropy function and 1D anisotropy function were determined inside liquid water using MCNPX code and compared to those of other commercially available iodine sources. Results: The dose rate constant of this new source was found to be 0.983+0.015 cGyh(-1)U(-1) that was in good agreement with the TLD measured data (0.965 cGyh(-1)U(-1)). The 10 anisotropy function at 3, 5, and 7 cm radial distances were obtained as 0.954, 0.953 and 0.959, respectively. Conclusion: The results of this study showed that the dosimetric characteristics of this new brachytherapy source are comparable with those of other commercially available sources. Furthermore, the simulated parameters were in accordance with the previously measured ones. Therefore, the Monte Carlo calculated dosimetric parameters could be employed to obtain the dose distribution around this new brachytherapy source based on TG-43 (U1) protocol

A review on the application of 3d printing technology in radiotherapy for breast cancer

Breast cancer is considered as one of the main causes of cancer death in women. Early diagnosis and treatment, especially by modern technologies play major roles in management of breast cancer. Radiation therapy is known as one of the main treatment options for breast cancer. Nowadays, 3D printing technology is also used to rapidly construct objects with high quality. Many studies have shown the positive effects of this technology on the results of cancer radiation therapy. The aim of this study was to review the application of 3D printing technology in treatment of breast cancer by mega voltage electron and photon beams, including bolus, applicators, immobilizer devices, and compensators. Creating personalized treatment devices by 3D printing technology reduces treatment errors, therefore, the prescribed dose is increased in the treatment area and subsequently improves treatment outcomes. In spite of the valuable benefits of this technology, there are some disadvantages such as size limitations and the number of materials used for printing. Indeed, recent studies are trying to fix the shortcomings of 3D printing technologies in clinical applications. © 2020, Mazandaran University of Medical Sciences. All rights reserved

Monte Carlo based simulation of LIAC intraoperative radiotherapy accelerator along with beam shaper applicator

Intraoperative electron radiotherapy is one of the radiotherapy methods that delivers a high single fraction of radiation dose to the patient in one session during the surgery. Beam shaper applicator is one of the applicators that is recently employed with this radiotherapy method. This applicator has a considerable application in treatment of large tumors. In this study, the dosimetric characteristics of the electron beam produced by LIAC intraoperative radiotherapy accelerator in conjunction with this applicator have been evaluated through Monte Carlo simulation by MCNP code. The results showed that the electron beam produced by the beam shaper applicator would have the desirable dosimetric characteristics, so that the mentioned applicator can be considered for clinical purposes. Furthermore, the good agreement between the results of simulation and practical dosimetry, confirms the applicability of Monte Carlo method in determining the dosimetric parameters of electron beam  intraoperative radiotherap

Determination of dosimetric characteristics of irseed 125I brachytherapy source

Introduction: Low dose rate brachytherapy sources have been widely used for interstitial implants in tumor sites, particularly in prostate. Dosimetric characteristics of a new IrSeed 125I brachytherapy source have been determined using the LiF thermoluminescent dosimeter (TLD) chips. Materials and Methods: Dose rate constant, radial dose function, and anisotropy function around the IrSeed 125I source were measured in a plexiglass phantom using TLD-100 chips. A plexiglass slab phantom with dimensions of 30×30×7.3 cm3 was used to measure dose distribution around the source. Results: Dose rate constant was measured to be equal to 0.965±0.006 cGyh-1U-1. Radial dose function, anisotropy function, and geometry function have been presented as tabulated data for the IrSeed source. Conclusion: Basically, the dosimetric parameters presented here for this new IrSeed source have clinical and treatment planning applications

BTEX in indoor air of beauty salons: Risk assessment, levels and factors influencing their concentrations

Concentrations of benzene, toluene, ethylbenzene, and xylene (BTEX) were investigated in indoor air quality of 50 beauty salons in Ardabil, Iran (2017). Ten liters of air samples were collected from each salons regarding the recommended method and analyzed by GC-FID for BTEX concentration. Also, structural and operational conditions of the salons were studied with a self-designed questioner. The results of this study show that the mean concentration of benzene (32.40 ± 26.38) higher than the recommended levels by Health Canada, ANSES and HKSAR. Among the BTEX, ethylbenzene (62.38 ± 32.37) has the most concentrations in the salons. Subsequently, the cancer risk values in different age groups of birth to <6, 6 to <21, and 21 to <81 for benzene (1.83 × 10−3, 2.76 × 10−4 and 1.50 × 10−4, respectively) and ethylbenzene (4.9 × 10−4, 7.30 × 10−5 and 3.52 × 10−5, respectively) for long time exposure were drastically higher than the recommended levels. The results showed that the benzene concentration is significantly influenced by the structural and operational conditions of type of ventilation system, area of the salons, the number of people in the salon, number of services in the salons, and while doing of bridal makeup. © 2018 Elsevier Inc

F‌I‌N‌I‌T‌E E‌L‌E‌M‌E‌N‌T M‌O‌D‌E‌L‌I‌N‌G O‌F T‌I‌R‌E M‌O‌V‌E‌M‌E‌N‌T O‌N A S‌M‌A‌R‌T A‌S‌P‌H‌A‌L‌T P‌A‌V‌E‌M‌E‌N‌T A‌N‌D I‌N‌V‌E‌S‌T‌I‌G‌A‌T‌I‌O‌N O‌F D‌A‌M‌A‌G‌E R‌E‌C‌O‌V‌E‌R‌Y (H‌E‌A‌L‌I‌N‌G) E‌F‌F‌E‌C‌T O‌N I‌T‌S L‌I‌F‌E‌T‌I‌M‌E

T‌h‌e d‌e‌s‌t‌r‌u‌c‌t‌i‌o‌n o‌f a‌s‌p‌h‌a‌l‌t p‌a‌v‌e‌m‌e‌n‌t‌s i‌s o‌n‌e o‌f t‌h‌e b‌i‌g‌g‌e‌s‌t p‌r‌o‌b‌l‌e‌m‌s i‌n r‌o‌a‌d c‌o‌n‌s‌t‌r‌u‌c‌t‌i‌o‌n i‌n t‌h‌e w‌o‌r‌l‌d, w‌h‌i‌c‌h i‌n‌c‌u‌r‌s a h‌u‌g‌e a‌m‌o‌u‌n‌t o‌f a‌n‌n‌u‌a‌l r‌e‌b‌u‌i‌l‌d‌i‌n‌g. T‌h‌e h‌e‌a‌l‌i‌n‌g p‌r‌o‌c‌e‌s‌s t‌o r‌e‌c‌o‌v‌e‌r d‌a‌m‌a‌g‌e i‌s o‌n‌e o‌f t‌h‌e e‌f‌f‌e‌c‌t‌i‌v‌e m‌e‌t‌h‌o‌d‌s t‌o e‌x‌t‌e‌n‌d t‌h‌e l‌i‌f‌e o‌f t‌h‌e‌s‌e p‌a‌v‌e‌m‌e‌n‌t‌s, w‌h‌i‌c‌h h‌a‌s b‌e‌e‌n p‌r‌e‌s‌e‌n‌t‌e‌d b‌y r‌e‌s‌e‌a‌r‌c‌h‌e‌r‌s i‌n r‌e‌c‌e‌n‌t y‌e‌a‌r‌s. S‌e‌l‌f-h‌e‌a‌l‌i‌n‌g p‌o‌l‌y‌m‌e‌r‌s a‌r‌e a c‌l‌a‌s‌s o‌f s‌m‌a‌r‌t m‌a‌t‌e‌r‌i‌a‌l‌s t‌h‌a‌t, w‌i‌t‌h‌o‌u‌t t‌h‌e n‌e‌e‌d f‌o‌r e‌x‌t‌e‌r‌n‌a‌l s‌t‌i‌m‌u‌l‌a‌t‌i‌o‌n, c‌a‌n r‌e‌p‌a‌i‌r p‌a‌r‌t o‌f t‌h‌e d‌a‌m‌a‌g‌e g‌e‌n‌e‌r‌a‌t‌e‌d a‌s m‌i‌c‌r‌o‌c‌r‌a‌c‌k‌s a‌n‌d m‌i‌c‌r‌o‌v‌o‌i‌d‌s i‌n t‌h‌e‌i‌r m‌i‌c‌r‌o‌s‌t‌r‌u‌c‌t‌u‌r‌e‌s. A‌l‌o‌n‌g w‌i‌t‌h t‌h‌e p‌u‌r‌p‌o‌s‌e o‌f t‌h‌e s‌t‌u‌d‌y, i.e., i‌n‌v‌e‌s‌t‌i‌g‌a‌t‌i‌n‌g t‌h‌e e‌f‌f‌e‌c‌t o‌f h‌e‌a‌l‌i‌n‌g i‌n t‌h‌e l‌i‌f‌e‌t‌i‌m‌e o‌f a‌s‌p‌h‌a‌l‌t p‌a‌v‌e‌m‌e‌n‌t‌s, t‌h‌e e‌x‌p‌l‌i‌c‌i‌t t‌i‌m‌e-d‌i‌s‌c‌r‌e‌t‌e f‌o‌r‌m o‌f t‌h‌e t‌h‌e‌r‌m‌o‌d‌y‌n‌a‌m‌i‌c‌a‌l‌l‌y c‌o‌n‌s‌i‌s‌t‌e‌n‌t m‌o‌d‌e‌l i‌s p‌r‌e‌s‌e‌n‌t‌e‌d i‌n o‌r‌d‌e‌r t‌o b‌e u‌t‌i‌l‌i‌z‌e‌d i‌n a f‌i‌n‌i‌t‌e e‌l‌e‌m‌e‌n‌t A‌B‌A‌Q‌U‌S s‌o‌f‌t‌w‌a‌r‌e b‌y V‌U‌M‌A‌T s‌u‌b‌r‌o‌u‌t‌i‌n‌e. T‌h‌e d‌i‌s‌c‌r‌e‌t‌i‌z‌a‌t‌i‌o‌n m‌e‌t‌h‌o‌d m‌e‌n‌t‌i‌o‌n‌e‌d h‌e‌r‌e h‌a‌s b‌e‌n‌e‌f‌i‌t‌s s‌u‌c‌h a‌s l‌o‌w c‌a‌l‌c‌u‌l‌a‌t‌i‌o‌n c‌o‌s‌t‌s a‌n‌d h‌i‌g‌h r‌e‌l‌i‌a‌b‌i‌l‌i‌t‌y i‌n r‌e‌s‌p‌o‌n‌s‌e. T‌h‌e‌n, t‌h‌r‌e‌e-d‌i‌m‌e‌n‌s‌i‌o‌n‌a‌l m‌o‌d‌e‌l‌i‌n‌g o‌f g‌e‌n‌e‌r‌a‌l v‌e‌h‌i‌c‌l‌e‌s' t‌i‌r‌e h‌a‌s b‌e‌e‌n d‌o‌n‌e u‌s‌i‌n‌g h‌y‌p‌e‌r‌e‌l‌a‌s‌t‌i‌c a‌n‌d v‌i‌s‌c‌o‌e‌l‌a‌s‌t‌i‌c m‌a‌t‌e‌r‌i‌a‌l‌s i‌n o‌r‌d‌e‌r t‌o h‌a‌v‌e t‌h‌e d‌e‌s‌i‌r‌e‌d d‌e‌f‌o‌r‌m‌a‌t‌i‌o‌n o‌n t‌h‌e p‌a‌v‌e‌m‌e‌n‌t a‌f‌t‌e‌r a‌p‌p‌l‌y‌i‌n‌g t‌h‌e l‌o‌a‌d. I‌n t‌h‌e f‌o‌l‌l‌o‌w‌i‌n‌g, t‌o e‌v‌a‌l‌u‌a‌t‌e p‌e‌r‌m‌a‌n‌e‌n‌t d‌e‌f‌o‌r‌m‌a‌t‌i‌o‌n‌s (c‌o‌m‌m‌o‌n f‌a‌i‌l‌u‌r‌e‌s i‌n t‌h‌e a‌s‌p‌h‌a‌l‌t p‌a‌v‌e‌m‌e‌n‌t) a‌n‌d t‌h‌e e‌f‌f‌e‌c‌t o‌f t‌h‌e h‌e‌a‌l‌i‌n‌g p‌r‌o‌c‌e‌s‌s o‌n i‌t‌s d‌i‌l‌a‌t‌i‌o‌n, i‌t i‌s n‌e‌c‌e‌s‌s‌a‌r‌y t‌o s‌i‌m‌u‌l‌a‌t‌e i‌t‌s b‌e‌h‌a‌v‌i‌o‌r i‌n h‌i‌g‌h-c‌y‌c‌l‌e l‌o‌a‌d‌i‌n‌g‌s. I‌n o‌r‌d‌e‌r t‌o r‌e‌d‌u‌c‌e t‌h‌e c‌o‌s‌t a‌n‌d t‌i‌m‌e o‌f c‌o‌m‌p‌u‌t‌a‌t‌i‌o‌n, a‌n a‌l‌t‌e‌r‌n‌a‌t‌i‌v‌e m‌e‌t‌h‌o‌d h‌a‌s b‌e‌e‌n u‌s‌e‌d. I‌n t‌h‌i‌s m‌e‌t‌h‌o‌d, i‌n o‌r‌d‌e‌r t‌o s‌p‌e‌e‌d u‌p t‌h‌e g‌r‌o‌w‌t‌h o‌f d‌a‌m‌a‌g‌e a‌n‌d, a‌l‌s‌o, h‌e‌a‌l‌i‌n‌g e‌f‌f‌e‌c‌t, t‌i‌r‌e m‌o‌v‌i‌n‌g v‌e‌l‌o‌c‌i‌t‌y h‌a‌s d‌e‌c‌r‌e‌a‌s‌e‌d. T‌h‌i‌s m‌a‌y i‌n‌c‌r‌e‌a‌s‌e t‌h‌e t‌i‌m‌e o‌f l‌o‌a‌d‌i‌n‌g o‌n a‌s‌p‌h‌a‌l‌t; t‌h‌e‌r‌e‌f‌o‌r‌e, r‌a‌t‌e o‌f d‌a‌m‌a‌g‌e i‌n‌c‌r‌e‌a‌s‌e. I‌n t‌h‌i‌s s‌i‌m‌u‌l‌a‌t‌i‌o‌n‌s, t‌h‌e l‌i‌f‌e o‌f t‌h‌e a‌s‌p‌h‌a‌l‌t p‌a‌v‌e‌m‌e‌n‌t i‌s c‌o‌m‌p‌a‌r‌e‌d w‌i‌t‌h t‌h‌e e‌f‌f‌e‌c‌t o‌f h‌e‌a‌l‌i‌n‌g a‌n‌d w‌i‌t‌h‌o‌u‌t t‌h‌e e‌f‌f‌e‌c‌t. T‌h‌e r‌e‌s‌u‌l‌t‌s o‌b‌t‌a‌i‌n‌e‌d f‌r‌o‌m t‌h‌e s‌i‌m‌u‌l‌a‌t‌i‌o‌n‌s s‌h‌o‌w t‌h‌a‌t, b‌y a‌p‌p‌l‌y‌i‌n‌g t‌h‌e e‌f‌f‌e‌c‌t o‌f h‌e‌a‌l‌i‌n‌g, t‌h‌e g‌r‌o‌w‌t‌h r‌a‌t‌e o‌f d‌a‌m‌a‌g‌e a‌n‌d d‌e‌s‌t‌r‌u‌c‌t‌i‌o‌n‌s c‌a‌u‌s‌e‌d b‌y t‌h‌e p‌e‌r‌m‌a‌n‌e‌n‌t d‌e‌f‌o‌r‌m‌a‌t‌i‌o‌n o‌f t‌h‌e p‌a‌v‌e‌m‌e‌n‌t d‌e‌c‌r‌e‌a‌s‌e‌s, a‌n‌d t‌h‌e p‌a‌v‌e‌m‌e‌n‌t l‌i‌f‌e‌t‌i‌m‌e c‌a‌n b‌e i‌n‌c‌r‌e‌a‌s‌e‌d u‌p t‌o m‌o‌r‌e t‌h‌a‌n 70\%