Serological Characterization and Antimicrobial Susceptibility Patterns of Clinical Isolates of Salmonella from Patients Attending General Hospital, Funtua, Nigeria

Serological characterization and antimicrobial susceptibility patterns of clinical isolates of Salmonella were carried out for a period of 8-months to study the most frequently encountered serovars in salmonellosis and their antimicrobial susceptibility patterns. Two hundred and forty samples from both stool and blood specimens were collected from out patients attending General Hospital, Funtua, Katsina state of Nigeria. The samples were collected from patients diagnosed by clinicians of having either pyrexia, gastroenteritis or both. Samples were cultured, isolates identified and antibiotic susceptibility test was performed using standard procedures. The total number of 29(12.1%) of the 240 samples collected were identified as Salmonella strains. Out of the 29 isolates, 19(65.5%) were responsible for typhoidal salmonellosis while 10(34.5%) were responsible for non-typhoidal salmonellosis. Of the 29 cases of salmonellosis, 24(82.8%) were from children and 5(17.2.7%) from adults. However, the age of the patients have no significant relationship in both the typhoidal and non-typhoidal diseases, with their p values= 0.109, 0.784 > 0.05 respectively. S. typhi 16(55.2%) was the most frequently encountered, followed by S. enteritidis 7(24.1%) and 3(10.3%) each for S. paratyphi A and S. typhimurium. Of the total isolates, 26(89.7%) were found to be resistant to Ampicillin, 6(20.7%) resistant to Cefotaxime, 24(82.8%) resistant to Chloramphenicol, 9(31%) resistant to Co-trimoxazole and 2(6.9%) resistant to Nalidixic acid. However, resistance to Ofloxacin and Ciprofloxacin by the isolates were not observed. There was no statistically significant difference (p>0.05) in antimicrobial resistance patterns exhibited among typhoidal and non-typhoidal Salmonellae. Therefore, Fluoroquinolones are recommended as the drug of choice for both typhoidal and non-typhoidal salmonellosis, although, caution should be taken by the clinicians in prescribing them in order to avoid resistance to these drugs

Health facility-based survey of poliovirus antibody prevalence amongst children in Kebbi state, North west, Nigeria.

Background: High level of Poliovirus protective antibodies, must at all times be sustained in a community if poliomyelitis eradication is to be achieved. For some time now children have been vaccinated against poliomyelitis through various means in Northern Nigeria without authorities taking steps to evaluate the effectiveness of such activities. Aim: This research was focused on assessing the overall success of the Immunization programme using children whose mothers have access to immunization facilities. Materials and methods: A cross sectional survey was designed to enroll children whose mothers had access to Health Facilities across the state. Eighty blood samples of under - five years old children in Kebbi state were collected and tested for the presence of poliovirus antibodies. Indirect ELISA was used to detect for the presence of the antibodies. Results: Out of these samples collected, 65 (81.3%) have antibodies to all the serotypes. While 75 (93.8%), 71 (88.8%) and 74 (92.5%) have antibodies to poliovirus serotypes 1, 2 and 3 respectively. Older children 48 – 59 month had the highest poliovirus antibody prevalence 21 (95.5%). Female children had higher prevalence than males. Children who have not received any vaccination against Poliovirus had lowest antibody prevalence 9 (64.3%). Children who had more than four doses of the vaccine had the highest prevalence of Poliovirus antibodies. Urban children had higher Poliovirus antibody prevalence than their rural counterparts. Children whose fathers educational were up to tertiary level had higher antibody prevalence than those with either primary or secondary school level. Conclusion: This study found out that age of the children and educational level of the children fathers had a significant effect on the prevalence of antibodies at P = 0.05. More work needs to be done in order to sustain the apparent success achieved in stopping the poliovirus circulation and outbreaks within the populace in Kebbi state Nigeria.Keywords: Antibodies, Children, Kebbi State and Prevalence

Human immunodeficiency virus type-1 (HIV-1) genetic diversity and prevalence of antiretroviral drug resistance mutations in treatment-naïve adults in Jos, North Central Nigeria

The presence of human immunodeficiency virus (HIV) type-1 diversity has an impact on vaccine efficacy and drug resistance. It is important to know the circulating genetic variants and associated drug-resistance mutations in the context of scale up of antiretroviral therapy (ART) in Nigeria. The objective of this study was to determine the genetic diversity of HIV-1 and the prevalence of antiretroviral (ARV) drug resistance mutations among antiretroviral treatment-naïve HIV-1 infected patients in Jos, North Central Nigeria. Plasma samples were collected from 105 ARV drug-naïve patients enrolled for HIV care at the Jos University Teaching Hospital (JUTH) HIV Treatment Center between October 2010 and April 2011. One hundred (100) samples were successfully amplified. Viral subtyping was done using REGA subtyping tool and by phylogenetic analysis using PAUP software. The drug resistance mutations were determined using the Stanford University HIVdb sequence interpretation algorithm. HIV-1 subtypes identified were; CRF02_AG (48.0%), G (41.0%), CRF06_cpx (6.0%) and A1 (5.0%). 8% of the patients’ isolates had at least one major resistance mutation in the RT gene: Nucleoside reverse transcriptase inhibitors: M41L (1%), K65KR (1%), M184IM (1%), M184V (2%) and T215ADNT (1%), non-nucleoside reverse transcriptase inhibitors: K103N (2%), K101E (1%), G190A (1%), P225HP (1%), Y181I (1%), Y188L (1%), and Y181C (1%). Among antiretroviral (ARV) naïve patients in Jos, North Central Nigeria, the common HIV-1 subtypes was CRF_02 and G. And the prevalence of drug resistance mutations was found to be high (8%). Further study and national surveillance will be critically important to understand the clinical impact of transmitted resistance mutations on ART naïve individuals in resource limited settings.Keywords: HIV-1 subtypes, antiretroviral (ARV), treatment-naïve, drug-resistance, mutation, accessory and polymorphisms, NigeriaAfrican Journal of Biotechnology Vol. 12(17), pp. 2279-228

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

Antimicrobial susceptibility of neisseria gonorrhoeae isolated from patients attending private clinics in Zaria

A total of 125 Neisseria gonorrhoeae strains were isolated from patients attending private clinics in Zaria, Kaduna State, Nigeria. Out of the 125 gonococcal isolates, 90 (72%) were resistant to penicillin G, 85 (68%) to ampicillin, 70 (56%) to tetracycline, 55 (44%) to erythromycin and 26 (22%) isolates were resistant to gentamicin. All the 125 Neisseria gonorrhoeae isolates were susceptible to ceftriaxone, cefuroxime and ofloxacin. Out of the 90 Neisseria gonorrhoeae isolates resistant to penicillin, 65 (72.2%) were positive for β-lactamase production (PPNG). The remaining 25 (27.7%) penicillin resistant strains were β-lactamase negative. The findings of this study have shown high prevalence of multi-drug resistant strains of Neisseria gonorrhoeae amongst attendees of private clinics in Zaria. African Journal of Clinical Experimental Microbiology Vol. 8 (2) 2007: pp. 101-10

Prevalence and antimicrobial susceptibility of Neisseria gonorrhoeae isolated from patients in various locations of Kaduna state, Nigeria

Background/Method: A total of one thousand seven hundred and fifteen (1715) patients, consisting of nine hundred and thirty eight (938) female and seven hundred and seventy seven (777) male patients were screened for Neisseria gonorrhoeae infection from seven locations representing the four geographical zones of Kaduna State. Results: Out of the 1715 patients screened, 275 (16.03%) were found positive for N. gonorrhoeae infection. The prevalence rate of N. gonorrhoeae infection per location were in Zaria 70 (22.08), Kaduna 32 (21.33%), Pambeguwa 58 (18.35%), Kafanchan 25 (16.66%), Kachia 19 (12.66%), Giwa 31(11.70%), and Soba 34 (10.76%). Results showed that the age group 15-20 years had the highest prevalence of infection (31.05%) followed by the age group 36-40 years and 21-25 years with prevalence of 26.06% and 22.80% respectively. The highest prevalence in males (23.91%) occurred in the age group 36-40 years while the highest prevalence of infection in the female patients (11.18%) was found in the age group 15-20 years. Out of the 275 gonococcal isolates, 225 (81.82%) were resistant to penicillin, 206 (74.91%) to ampicillin, 122(44.36%) to tetracycline, 34(12.36%) isolates to erythromycin, and 16(5.82%) isolates were resistant to gentamicin. All the 275 N. gonorrhoeae isolates were sensitive to Ceftriaxone, Ceproxine and Oflozacin. Out of the 225 penicillin resistant strains of N. gonorrhoeae189 (84%) were positive for beta-lactamase production. The prevalence of beta-lactamase (Penicillinase) producing N.gonorrhoeae (PPNG), was statistically significant with X2 = 12.25 which was greater than X2t value. Generally there was high prevalence rate of N.gonorrhoeae infection in Kaduna State and the Conclusion: N. gonorrhoeaeisolates were highly resistant to most commonly used antibiotics in the treatment of gonorrhoea in Kaduna State. (Nig J Surg Res 2003; 5: 50 – 56) Key words: Gonorrhoea, antibiotic susceptibility, treatmen

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

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

BackgroundEstimates 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.Methods22 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.FindingsGlobal 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.InterpretationGlobal 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