21 research outputs found
Genomic epidemiology and the role of international and regional travel in the SARS-CoV-2 epidemic in Zimbabwe: a retrospective study of routinely collected surveillance data.
BACKGROUND: Advances in SARS-CoV-2 sequencing have enabled identification of new variants, tracking of its evolution, and monitoring of its spread. We aimed to use whole genome sequencing to describe the molecular epidemiology of the SARS-CoV-2 outbreak and to inform the implementation of effective public health interventions for control in Zimbabwe. METHODS: We performed a retrospective study of nasopharyngeal samples collected from nine laboratories in Zimbabwe between March 20 and Oct 16, 2020. Samples were taken as a result of quarantine procedures for international arrivals or to test for infection in people who were symptomatic or close contacts of positive cases. Samples that had a cycle threshold of less than 30 in the diagnostic PCR test were processed for sequencing. We began our analysis in July, 2020 (120 days since the first case), with a follow-up in October, 2020 (at 210 days since the first case). The phylogenetic relationship of the genome sequences within Zimbabwe and global samples was established using maximum likelihood and Bayesian methods. FINDINGS: Of 92 299 nasopharyngeal samples collected during the study period, 8099 were PCR-positive and 328 were available for sequencing, with 156 passing sequence quality control. 83 (53%) of 156 were from female participants. At least 26 independent introductions of SARS-CoV-2 into Zimbabwe in the first 210 days were associated with 12 global lineages. 151 (97%) of 156 had the Asp614Gly mutation in the spike protein. Most cases, 93 (60%), were imported from outside Zimbabwe. Community transmission was reported 6 days after the onset of the outbreak. INTERPRETATION: Initial public health interventions delayed onset of SARS-CoV-2 community transmission after the introduction of the virus from international and regional migration in Zimbabwe. Global whole genome sequence data are essential to reveal major routes of spread and guide intervention strategies. FUNDING: WHO, Africa CDC, Biotechnology and Biological Sciences Research Council, Medical Research Council, National Institute for Health Research, and Genome Research Limited.WHO, Africa CDC, Biotechnology and Biological Sciences Research Council, Medical Research Council, National Institute for Health Research, and Genome Research Limite
Distribution of schistosomiasis and soil transmitted Helminthiasis in Zimbabwe:Towards a national plan of action for control and elimination
Schistosomiasis and STH are among the list of neglected tropical diseases considered for control by the WHO. Although both diseases are endemic in Zimbabwe, no nationwide control interventions have been implemented. For this reason in 2009 the Zimbabwe Ministry of Health and Child Care included the two diseases in the 2009-2013 National Health Strategy highlighting the importance of understanding the distribution and burden of the diseases as a prerequisite for elimination interventions. It is against this background that a national survey was conducted.A countrywide cross-sectional survey was carried out in 280 primary schools in 68 districts between September 2010 and August 2011. Schistosoma haematobium was diagnosed using the urine filtration technique. Schistosoma mansoni and STH (hookworms, Trichuris trichiura, Ascaris lumbricoides) were diagnosed using both the Kato Katz and formol ether concentration techniques.Schistosomiasis was more prevalent country-wide (22.7%) than STH (5.5%). The prevalence of S. haematobium was 18.0% while that of S. mansoni was 7.2%. Hookworms were the most common STH with a prevalence of 3.2% followed by A. lumbricoides and T. trichiura with prevalence of 2.5% and 0.1%, respectively. The prevalence of heavy infection intensity as defined by WHO for any schistosome species was 5.8% (range 0%-18.3% in districts). Only light to moderate infection intensities were observed for STH species. The distribution of schistosomiasis and STH varied significantly between provinces, districts and schools (p<0.001). Overall, the prevalence of co-infection with schistosomiasis and STH was 1.5%. The actual co-endemicity of schistosomiasis and STH was observed in 43 (63.2%) of the 68 districts screened.This study provided comprehensive baseline data on the distribution of schistosomiasis and STH that formed the basis for initiating a national control and elimination programme for these two neglected tropical diseases in Zimbabwe
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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
The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance
INTRODUCTION
Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic.
RATIONALE
We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs).
RESULTS
Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants.
CONCLUSION
Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century
Inclusion of edaphic predictors for enhancement of models to determine distribution of soil-transmitted helminths: the case of Zimbabwe
Abstract Background Reliable mapping of soil-transmitted helminth (STH) parasites requires rigorous statistical and machine learning algorithms capable of integrating the combined influence of several determinants to predict distributions. This study tested whether combining edaphic predictors with relevant environmental predictors improves model performance when predicting the distribution of STH, Ascaris lumbricoides and hookworms at a national scale in Zimbabwe. Methods Geo-referenced parasitological data obtained from a 2010/2011 national survey indicating a confirmed presence or absence of STH among school children aged 10–15 years was used to calibrate ten species distribution models (SDMs). The performance of SDMs calibrated with a set of environmental and edaphic variables was compared to that of SDMs calibrated with environmental variables only. Model performance was evaluated using the true skill statistic and receiver operating characteristic curve. Results Results show a significant improvement in model performance for both A. lumbricoides and hookworms for all ten SDMs after edaphic variables were combined with environmental variables in the modelling of the geographical distribution of the two STHs at national scale. Using the top three performing models, a consensus prediction was developed to generate the first continuous maps of the potential distribution of the two STHs in Zimbabwe. Conclusions The findings from this study demonstrate significant model improvement if relevant edaphic variables are included in model calibration resulting in more accurate mapping of STH. The results also provide spatially-explicit information to aid targeted control of STHs in Zimbabwe and other countries with STH burden
Prevalence distribution of schistosomiasis and STH among 13, 038 primary school children by settlement in Zimbabwe during 2011 school calendar.
<p>(HD = High density; LD = Low density)</p
Prevalence of combined schistosomiasis and STH infection by province in Zimbabwe in 2011.
<p><b>* = </b> Chitungwiza is not a metropolitan province but a town.</p
Prevalence of infection intensities of schistosome species and heavy infection with any schistosome species in Zimbabwe stratified by gender and province in 2011.
<p>* = Number examined</p><p><b>¤</b> = Chitungwiza is not a metropolitan province but a town</p
Prevalence of schistosomiasis and soil transmitted helminthiasis co-infection combinationsby province in Zimbabwe in 2011.
<p>Prevalence of schistosomiasis and soil transmitted helminthiasis co-infection combinationsby province in Zimbabwe in 2011.</p
Stratification of 68 districts in Zimbabwe according to prevalence of heavy infection with any schistosome species (morbidity) and the proposed intervention strategies in 2011.
<p><b>Key:</b></p><p>Complementary strategies = Health education, safe water and sanitation, environmental management and snail control.</p