Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design.

Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases.

An Ensemble Framework for Projecting the Impact of Lymphatic Filariasis Interventions Across Sub-Saharan Africa at a Fine Spatial Scale.

BACKGROUND: Lymphatic filariasis (LF) is a neglected tropical disease targeted for elimination as a public health problem by 2030. Although mass treatments have led to huge reductions in LF prevalence, some countries or regions may find it difficult to achieve elimination by 2030 owing to various factors, including local differences in transmission. Subnational projections of intervention impact are a useful tool in understanding these dynamics, but correctly characterizing their uncertainty is challenging. METHODS: We developed a computationally feasible framework for providing subnational projections for LF across 44 sub-Saharan African countries using ensemble models, guided by historical control data, to allow assessment of the role of subnational heterogeneities in global goal achievement. Projected scenarios include ongoing annual treatment from 2018 to 2030, enhanced coverage, and biannual treatment. RESULTS: Our projections suggest that progress is likely to continue well. However, highly endemic locations currently deploying strategies with the lower World Health Organization recommended coverage (65%) and frequency (annual) are expected to have slow decreases in prevalence. Increasing intervention frequency or coverage can accelerate progress by up to 5 or 6 years, respectively. CONCLUSIONS: While projections based on baseline data have limitations, our methodological advancements provide assessments of potential bottlenecks for the global goals for LF arising from subnational heterogeneities. In particular, areas with high baseline prevalence may face challenges in achieving the 2030 goals, extending the "tail" of interventions. Enhancing intervention frequency and/or coverage will accelerate progress. Our approach facilitates preimplementation assessments of the impact of local interventions and is applicable to other regions and neglected tropical diseases.

Model-based geostatistical design and analysis of prevalence for soil-transmitted helminths in Kenya: Results from ten-years of the Kenya national school-based deworming programme.

Background: Kenya is endemic for soil-transmitted helminths (STH) with over 6 million children in 27 counties currently at-risk. A national school-based deworming programme (NSBDP) was launched in 2012 with a goal to eliminate parasitic worms as a public health problem. This study used model-based geostatistical (MBG) approach to design and analyse the impact of the NSBDP and inform treatment strategy changes. Methods: A cross-sectional study was used to survey 200 schools across 27 counties in Kenya. The study design, school selection and analysis followed the MBG approach which incorporated historical data on treatment, morbidity and environmental covariates to efficiently predict the helminths prevalence in Kenya. Results: Overall, the NSBDP geographic area prevalence for any STH was estimated to sit between 2 % and <10 % with a high predictive probability of >0.999. Species-specific thresholds were between 2 % and <10 % for Ascaris lumbricoides, 0 % to <2 % for hookworm, and 0 % to <2 % for Trichuris trichiura, all with high predictive probability of >0.999. Conclusions: Based on the World Health Organization guidelines, STH treatment requirements can now be confidently refined. Ten counties may consider suspending treatment and implement appropriate surveillance system, while another 10 will require treatment once every two years, and the remaining seven will require treatment once every year.

Modernizing the design and analysis of prevalence surveys for neglected tropical diseases.

Current WHO guidelines set prevalence thresholds below which a neglected tropical disease can be considered to have been eliminated as a public health problem, and specify how surveys to assess whether elimination has been achieved should be designed and analysed, based on classical survey sampling methods. In this paper, we describe an alternative approach based on geospatial statistical modelling. We first show the gains in efficiency that can be obtained by exploiting any spatial correlation in the underlying prevalence. We then suggest that the current guidelines' implicit use of a significance testing argument is not appropriate; instead, we argue for a predictive inferential framework, leading to design criteria based on controlling the rates at which areas whose true prevalence lies above and below the elimination threshold are incorrectly classified. We describe how this approach naturally accommodates context-specific information in the form of georeferenced covariates that have been shown to be predictive of disease prevalence. Finally, we give a progress report of an ongoing collaboration with the Guyana Ministry of Health Neglected Tropical Disease programme on the design of an IDA (ivermectin, diethylcarbamazine and albendazole) Impact Survey of lymphatic filariasis to be conducted in Guyana in early 2023. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.

Neonatal Paenibacilliosis: Paenibacillus Infection as a Novel Cause of Sepsis in Term Neonates With High Risk of Sequelae in Uganda.

BACKGROUND: Paenibacillus thiaminolyticus may be an underdiagnosed cause of neonatal sepsis. METHODS: We prospectively enrolled a cohort of 800 full-term neonates presenting with a clinical diagnosis of sepsis at 2 Ugandan hospitals. Quantitative polymerase chain reaction specific to P. thiaminolyticus and to the Paenibacillus genus were performed on the blood and cerebrospinal fluid (CSF) of 631 neonates who had both specimen types available. Neonates with Paenibacillus genus or species detected in either specimen type were considered to potentially have paenibacilliosis, (37/631, 6%). We described antenatal, perinatal, and neonatal characteristics, presenting signs, and 12-month developmental outcomes for neonates with paenibacilliosis versus clinical sepsis due to other causes. RESULTS: Median age at presentation was 3 days (interquartile range 1, 7). Fever (92%), irritability (84%), and clinical signs of seizures (51%) were common. Eleven (30%) had an adverse outcome: 5 (14%) neonates died during the first year of life; 5 of 32 (16%) survivors developed postinfectious hydrocephalus (PIH) and 1 (3%) additional survivor had neurodevelopmental impairment without hydrocephalus. CONCLUSIONS: Paenibacillus species was identified in 6% of neonates with signs of sepsis who presented to 2 Ugandan referral hospitals; 70% were P. thiaminolyticus. Improved diagnostics for neonatal sepsis are urgently needed. Optimal antibiotic treatment for this infection is unknown but ampicillin and vancomycin will be ineffective in many cases. These results highlight the need to consider local pathogen prevalence and the possibility of unusual pathogens when determining antibiotic choice for neonatal sepsis.

Paenibacillus spp infection among infants with postinfectious hydrocephalus in Uganda: an observational case-control study.

BACKGROUND: Paenibacillus thiaminolyticus is a cause of postinfectious hydrocephalus among Ugandan infants. To determine whether Paenibacillus spp is a pathogen in neonatal sepsis, meningitis, and postinfectious hydrocephalus, we aimed to complete three separate studies of Ugandan infants. The first study was on peripartum prevalence of Paenibacillus in mother-newborn pairs. The second study assessed Paenibacillus in blood and cerebrospinal fluid (CSF) from neonates with sepsis. The third study assessed Paenibacillus in CSF from infants with hydrocephalus. METHODS: In this observational study, we recruited mother-newborn pairs with and without maternal fever (mother-newborn cohort), neonates (aged ≤28 days) with sepsis (sepsis cohort), and infants (aged ≤90 days) with hydrocephalus with and without a history of neonatal sepsis and meningitis (hydrocephalus cohort) from three hospitals in Uganda between Jan 13, 2016 and Oct 2, 2019. We collected maternal blood, vaginal swabs, and placental samples and the cord from the mother-newborn pairs, and blood and CSF from neonates and infants. Bacterial content of infant CSF was characterised by 16S rDNA sequencing. We analysed all samples using quantitative PCR (qPCR) targeting either the Paenibacillus genus or Paenibacillus thiaminolyticus spp. We collected cranial ultrasound and computed tomography images in the subset of participants represented in more than one cohort. FINDINGS: No Paenibacillus spp were detected in vaginal, maternal blood, placental, or cord blood specimens from the mother-newborn cohort by qPCR. Paenibacillus spp was detected in 6% (37 of 631 neonates) in the sepsis cohort and, of these, 14% (5 of 37 neonates) developed postinfectious hydrocephalus. Paenibacillus was the most enriched bacterial genera in postinfectious hydrocephalus CSF (91 [44%] of 209 patients) from the hydrocephalus cohort, with 16S showing 94% accuracy when validated by qPCR. Imaging showed progression from Paenibacillus spp-related meningitis to postinfectious hydrocephalus over 1-3 months. Patients with postinfectious hydrocephalus with Paenibacillus spp infections were geographically clustered. INTERPRETATION: Paenibacillus spp causes neonatal sepsis and meningitis in Uganda and is the dominant cause of subsequent postinfectious hydrocephalus. There was no evidence of transplacental transmission, and geographical evidence was consistent with an environmental source of neonatal infection. Further work is needed to identify routes of infection and optimise treatment of neonatal Paenibacillus spp infection to lessen the burden of morbidity and mortality. FUNDING: National Institutes of Health and Boston Children's Hospital Office of Faculty Development.

Estimating the burden of mycetoma in Sudan for the period 1991-2018 using a model-based geostatistical approach.

Mycetoma is widespread in tropical and subtropical regions favouring arid areas with low humidity and a short rainy season. Sudan is one of the highly endemic countries for mycetoma. Estimating the population at risk and the number of cases is critical for delivering targeted and equitable prevention and treatment services. In this study, we have combined a large dataset of mycetoma cases recorded by the Mycetoma Research Centre (MRC) in Sudan over 28 years (1991-2018) with a collection of environmental and water and hygiene-related datasets in a geostatistical framework to produce estimates of the disease burden across the country. We developed geostatistical models to predict the number of cases of actinomycetoma and eumycetoma in areas considered environmentally suitable for the two mycetoma forms. Then used the raster dataset (gridded map) with the population estimates for 2020 to compute the potentially affected population since 1991. The geostatistical models confirmed this heterogeneous and distinct distribution of the estimated cases of eumycetoma and actinomycetoma across Sudan. For eumycetoma, these higher-risk areas were smaller and scattered across Al Jazirah, Khartoum, White Nile and Sennar states, while for actinomycetoma a higher risk for infection is shown across the rural districts of North and West Kurdufan. Nationally, we estimated 63,825 people (95%CI: 13,693 to 197,369) to have been suffering from mycetoma since 1991 in Sudan,51,541 people (95%CI: 9,893-166,073) with eumycetoma and 12,284 people (95%CI: 3,800-31,296) with actinomycetoma. In conclusion, the risk of mycetoma in Sudan is particularly high in certain restricted areas, but cases are ubiquitous across all states. Both prevention and treatment services are required to address the burden. Such work provides a guide for future control and prevention programs for mycetoma, highly endemic areas are clearly targeted, and resources are directed to areas with high demand.

Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020.

Objective: Cancer incidence and mortality rates in Africa are increasing, yet their geographic distribution and determinants are incompletely characterized. The present study aims to establish the spatial epidemiology of cancer burden in Africa and delineate the association between cancer burden and the country-level socioeconomic status. The study also examines the forecasts of the cancer burden for 2040 and evaluates infrastructure availability across all African countries. Methods: The estimates of age, sex, and country-specific incidence and mortality of 34 neoplasms in 54 African countries, were procured from GLOBOCAN 2020. Mortality-to-incidence ratio (MIR) was employed as a proxy indicator of 5-year survival rates, and the socioeconomic development of each country was measured using its human development index (HDI). We regressed age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and MIR on HDI using linear regression model to determine the relationship between cancer burden and HDI. Maps were generated for each cancer group for each country in Africa. The data about the cancer infrastructure of African countries were extracted from the WHO Cancer Country Profiles. Results: In Africa, an estimated 1.1 million new cases [95% uncertainty intervals (UIs) 1.0 - 1.3 million] and 711,429 [611,604 - 827,547] deaths occurred due to neoplasms in 2020. The ASIR was estimated to be 132.1/100,000, varying from 78.4/100,000 (Niger) to 212.5/100,000 (La Réunion) in 2020. The ASMR was 88.8/100,000 in Africa, ranging from 56.6/100,000 in the Republic of the Congo to 139.4/100,000 in Zimbabwe. The MIR of all cancer combined was 0.64 in Africa, varying from 0.49 in Mauritius to 0.78 in The Gambia. HDI had a significant negative correlation with MIR of all cancer groups combined and main cancer groups (prostate, breast, cervical and colorectal). HDI explained 75% of the variation in overall 5-year cancer survival (MIR). By 2040, the burden of all neoplasms combined is forecasted to increase to 2.1 million new cases and 1.4 million deaths in Africa. Conclusion: High cancer mortality rates in Africa demand a holistic approach toward cancer control and management, including, but not limited to, boosting cancer awareness, adopting primary and secondary prevention, mitigating risk factors, improving cancer infrastructure and timely treatment.

Geostatistical modelling enables efficient safety assessment for mass drug administration with ivermectin in Loa loa endemic areas through a combined antibody and LoaScope testing strategy for elimination of onchocerciasis.

The elimination of onchocerciasis through community-based Mass Drug Administration (MDA) of ivermectin (Mectizan) is hampered by co-endemicity of Loa loa, as individuals who are highly co-infected with Loa loa parasites can suffer serious and occasionally fatal neurological reactions from the drug. The test-and-not-treat strategy of testing all individuals participating in MDA has some operational constraints including the cost and limited availability of LoaScope diagnostic tools. As a result, a Loa loa Antibody (Ab) Rapid Test was developed to offer a complementary way of determining the prevalence of loiasis. We develop a joint geostatistical modelling framework for the analysis of Ab and Loascope data to delineate whether an area is safe for MDA. Our results support the use of a two-stage strategy, in which Ab testing is used to identify areas that, with acceptably high probability, are safe or unsafe for MDA, followed by Loascope testing in areas whose safety status is uncertain. This work therefore contributes to the global effort towards the elimination of onchocerciasis as a public health problem by potentially reducing the time and cost required to establish whether an area is safe for MDA.

Cytomegalovirus infections in infants in Uganda: Newborn-mother pairs, neonates with sepsis, and infants with hydrocephalus.

OBJECTIVES: To estimate the prevalence of cytomegalovirus (CMV) infections among newborn-mother pairs, neonates with sepsis, and infants with hydrocephalus in Uganda. DESIGN AND METHODS: Three populations-newborn-mother pairs, neonates with sepsis, and infants (≤3 months) with nonpostinfectious (NPIH) or postinfectious (PIH) hydrocephalus-were evaluated for CMV infection at 3 medical centers in Uganda. Quantitative PCR (qPCR) was used to characterize the prevalence of CMV. RESULTS: The overall CMV prevalence in 2498 samples across all groups was 9%. In newborn-mother pairs, there was a 3% prevalence of cord blood CMV positivity and 33% prevalence of maternal vaginal shedding. In neonates with clinical sepsis, there was a 2% CMV prevalence. Maternal HIV seropositivity (adjusted odds ratio [aOR] 25.20; 95% confidence interval [CI] 4.43-134.26; p = 0.0001), residence in eastern Uganda (aOR 11.06; 95% CI 2.30-76.18; p = 0.003), maternal age <25 years (aOR 4.54; 95% CI 1.40-19.29; p = 0.02), and increasing neonatal age (aOR 1.08 for each day older; 95% CI 1.00-1.16; p = 0.05), were associated risk factors for CMV in neonates with clinical sepsis. We found a 2-fold higher maternal vaginal shedding in eastern (45%) vs western (22%) Uganda during parturition (n = 22/49 vs 11/50, the Fisher exact test; p = 0.02). In infants with PIH, the prevalence in blood was 24% and in infants with NPIH, it was 20%. CMV was present in the cerebrospinal fluid (CSF) of 13% of infants with PIH compared with 0.5% of infants with NPIH (n = 26/205 vs 1/194, p < 0.0001). CONCLUSIONS: Our findings highlight that congenital and postnatal CMV prevalence is substantial in this African setting, and the long-term consequences are uncharacterized.

SARS-CoV-2 infection and vaccine effectiveness in England (REACT-1): a series of cross-sectional random community surveys.

BACKGROUND: England has experienced a third wave of the COVID-19 epidemic since the end of May, 2021, coinciding with the rapid spread of the delta (B.1.617.2) variant, despite high levels of vaccination among adults. Vaccination rates (single dose) in England are lower among children aged 16-17 years and 12-15 years, whose vaccination in England commenced in August and September, 2021, respectively. We aimed to analyse the underlying dynamics driving patterns in SARS-CoV-2 prevalence during September, 2021, in England. METHODS: The REal-time Assessment of Community Transmission-1 (REACT-1) study, which commenced data collection in May, 2020, involves a series of random cross-sectional surveys in the general population of England aged 5 years and older. Using RT-PCR swab positivity data from 100 527 participants with valid throat and nose swabs in round 14 of REACT-1 (Sept 9-27, 2021), we estimated community-based prevalence of SARS-CoV-2 and vaccine effectiveness against infection by combining round 14 data with data from round 13 (June 24 to July 12, 2021; n=172 862). FINDINGS: During September, 2021, we estimated a mean RT-PCR positivity rate of 0·83% (95% CrI 0·76-0·89), with a reproduction number (R) overall of 1·03 (95% CrI 0·94-1·14). Among the 475 (62·2%) of 764 sequenced positive swabs, all were of the delta variant; 22 (4·63%; 95% CI 3·07-6·91) included the Tyr145His mutation in the spike protein associated with the AY.4 sublineage, and there was one Glu484Lys mutation. Age, region, key worker status, and household size jointly contributed to the risk of swab positivity. The highest weighted prevalence was observed among children aged 5-12 years, at 2·32% (95% CrI 1·96-2·73) and those aged 13-17 years, at 2·55% (2·11-3·08). The SARS-CoV-2 epidemic grew in those aged 5-11 years, with an R of 1·42 (95% CrI 1·18-1·68), but declined in those aged 18-54 years, with an R of 0·81 (0·68-0·97). At ages 18-64 years, the adjusted vaccine effectiveness against infection was 62·8% (95% CI 49·3-72·7) after two doses compared to unvaccinated people, for all vaccines combined, 44·8% (22·5-60·7) for the ChAdOx1 nCov-19 (Oxford-AstraZeneca) vaccine, and 71·3% (56·6-81·0) for the BNT162b2 (Pfizer-BioNTech) vaccine. In individuals aged 18 years and older, the weighted prevalence of swab positivity was 0·35% (95% CrI 0·31-0·40) if the second dose was administered up to 3 months before their swab but 0·55% (0·50-0·61) for those who received their second dose 3-6 months before their swab, compared to 1·76% (1·60-1·95) among unvaccinated individuals. INTERPRETATION: In September, 2021, at the start of the autumn school term in England, infections were increasing exponentially in children aged 5-17 years, at a time when vaccination rates were low in this age group. In adults, compared to those who received their second dose less than 3 months ago, the higher prevalence of swab positivity at 3-6 months following two doses of the COVID-19 vaccine suggests an increased risk of breakthrough infections during this period. The vaccination programme needs to reach children as well as unvaccinated and partially vaccinated adults to reduce SARS-CoV-2 transmission and associated disruptions to work and education. FUNDING: Department of Health and Social Care, England.

Model-based geostatistics enables more precise estimates of neglected tropical-disease prevalence in elimination settings: mapping trachoma prevalence in Ethiopia.

BACKGROUND: As the prevalences of neglected tropical diseases reduce to low levels in some countries, policymakers require precise disease estimates to decide whether the set public health targets have been met. At low prevalence levels, traditional statistical methods produce imprecise estimates. More modern geospatial statistical methods can deliver the required level of precision for accurate decision-making. METHODS: Using spatially referenced data from 3567 cluster locations in Ethiopia in the years 2017, 2018 and 2019, we developed a geostatistical model to estimate the prevalence of trachomatous trichiasis and to calculate the probability that the trachomatous trichiasis component of the elimination of trachoma as a public health problem has already been achieved for each of 482 evaluation units. We also compared the precision of traditional and geostatistical approaches by the ratios of the lengths of their 95% predictive intervals. RESULTS: The elimination threshold of trachomatous trichiasis (prevalence ≤ 0.2% in individuals aged ≥15 years) is met with a probability of 0.9 or more in 8 out of the 482 evaluation units assessed, and with a probability of ≤0.1 in 469 evaluation units. For the remaining five evaluation units, the probability of elimination is between 0.45 and 0.65. Prevalence estimates were, on average, 10 times more precise than estimates obtained using the traditional approach. CONCLUSIONS: By accounting for and exploiting spatial correlation in the prevalence data, we achieved remarkably improved precision of prevalence estimates compared with the traditional approach. The geostatistical approach also delivers predictions for unsampled evaluation units that are geographically close to sampled evaluation units.

MBGapp: A Shiny application for teaching model-based geostatistics to population health scientists.

User-friendly interfaces have been increasingly used to facilitate the learning of advanced statistical methodology, especially for students with only minimal statistical training. In this paper, we illustrate the use of MBGapp for teaching geostatistical analysis to population health scientists. Using a case-study on Loa loa infections, we show how MBGapp can be used to teach the different stages of a geostatistical analysis in a more interactive fashion. For wider accessibility and usability, MBGapp is available as an R package and as a Shiny web-application that can be freely accessed on any web browser. In addition to MBGapp, we also present an auxiliary Shiny app, called VariagramApp, that can be used to aid the teaching of Gaussian processes in one and two dimensions using simulations.

Exponential growth, high prevalence of SARS-CoV-2, and vaccine effectiveness associated with the Delta variant.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections were rising during early summer 2021 in many countries as a result of the Delta variant. We assessed reverse transcription polymerase chain reaction swab positivity in the Real-time Assessment of Community Transmission­1 (REACT-1) study in England. During June and July 2021, we observed sustained exponential growth with an average doubling time of 25 days, driven by complete replacement of the Alpha variant by Delta and by high prevalence at younger, less-vaccinated ages. Prevalence among unvaccinated people [1.21% (95% credible interval 1.03%, 1.41%)] was three times that among double-vaccinated people [0.40% (95% credible interval 0.34%, 0.48%)]. However, after adjusting for age and other variables, vaccine effectiveness for double-vaccinated people was estimated at between ~50% and ~60% during this period in England. Increased social mixing in the presence of Delta had the potential to generate sustained growth in infections, even at high levels of vaccination.

Spatial distribution and risk factors for human cysticercosis in Colombia.

BACKGROUND: Cysticercosis is a zoonotic neglected tropical disease (NTD) that affects humans and pigs following the ingestion of Taenia solium eggs. Human cysticercosis poses a substantial public health burden in endemic countries. The World Health Organization (WHO) aims to target high-endemicity settings with enhanced interventions in 17 countries by 2030. Between 2008 and 2010, Colombia undertook a national baseline serosurvey of unprecedented scale, which led to an estimated seroprevalence of T. solium cysticercus antibodies among the general population of 8.6%. Here, we use contemporary geostatistical approaches to analyse this unique dataset with the aim of understanding the spatial distribution and risk factors associated with human cysticercosis in Colombia to inform how best to target intervention strategies. METHODS: We used a geostatistical model to estimate individual and household risk factors associated with seropositivity to T. solium cysticercus antibodies from 29,253 people from 133 municipalities in Colombia. We used both independent and spatially structured random effects at neighbourhood/village and municipality levels to account for potential clustering of exposure to T. solium. We present estimates of the distribution and residual correlation of seropositivity at the municipality level. RESULTS: High seroprevalence was identified in municipalities located in the north and south of Colombia, with spatial correlation in seropositivity estimated up to approximately 140 km. Statistically significant risk factors associated with seropositivity to T. solium cysticercus were related to age, sex, educational level, socioeconomic status, use of rainwater, consumption of partially cooked/raw pork meat and possession of dogs. CONCLUSIONS: In Colombia, the distribution of human cysticercosis is influenced by socioeconomic considerations, education and environmental factors related to the spread of T. solium eggs. This information can be used to tailor national intervention strategies, such as targeting spatial hotspots and more highly exposed groups, including displaced people and women. Large-scale seroprevalence surveys accompanied by geospatial mapping are an essential step towards reaching the WHO's 2021‒2030 NTD roadmap targets.

Gun violence incidence during the COVID-19 pandemic is higher than before the pandemic in the United States.

During the coronavirus disease 2019 (COVID-19) pandemic, gun violence (GV) in the United States (U.S.) was postulated to increase strain on already taxed healthcare resources, such as blood products, intensive care beds, personal protective equipment, and even hospital staff. This report aims to estimate the relative risk of GV in the U.S. during the pandemic compared to before the pandemic. Daily police reports corresponding to gun-related injuries and deaths in the 50 states and the District of Columbia from February 1st, 2019, to March 31st, 2021 were obtained from the GV Archive. Generalized linear mixed-effects models in the form of Poisson regression analysis were utilized to estimate the state-specific rates of GV. Nationally, GV rates were 30% higher between March 01, 2020, and March 31, 2021 (during the pandemic), compared to the same period in 2019 (before the pandemic) [intensity ratio (IR) = 1.30; 95% CI 1.29, 1.32; p < 0.0001]. The risk of GV was significantly higher in 28 states and significantly lower in only one state. National and state-specific rates of GV were higher during the COVID-19 pandemic compared to the same timeframe 1 year prior. State-specific steps to mitigate violence, or at a minimum adequately prepare for its toll during the COVID-19 pandemic, should be taken.

Congenital Cytomegalovirus Infection Burden and Epidemiologic Risk Factors in Countries With Universal Screening: A Systematic Review and Meta-analysis.

Importance: Congenital cytomegalovirus (cCMV) infection is the most common congenital infection and the leading acquired cause of developmental disabilities and sensorineural deafness, yet a reliable assessment of the infection burden is lacking. Objectives: To estimate the birth prevalence of cCMV in low- and middle-income countries (LMICs) and high-income countries (HICs), characterize the rate by screening methods, and delineate associated risk factors of the infection. Data Sources: MEDLINE/PubMed, Scopus, and Cochrane Database of Systematic Reviews databases were searched from January 1, 1960, to March 1, 2021, and a total of 1322 studies were identified. Study Selection: Studies that provided data on the prevalence of cCMV derived from universal screening of infants younger than 3 weeks were included. Targeted screening studies were excluded. Data Extraction and Synthesis: Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline was followed. Extraction was performed independently by 3 reviewers. Quality was assessed using the Newcastle-Ottawa Scale for cohort studies. Random-effects meta-analysis was undertaken. Metaregression was conducted to evaluate the association of sociodemographic characteristics, maternal seroprevalence, population-level HIV prevalence, and screening methods with the prevalence of cCMV. Main Outcomes and Measures: Birth prevalence of cCMV ascertained through universal screening of infants younger than 3 weeks for CMV from urine, saliva, or blood samples. Results: Seventy-seven studies comprising 515 646 infants met the inclusion criteria from countries representative of each World Bank income level. The estimated pooled overall prevalence of cCMV was 0.67% (95% CI, 0.54%-0.83%). The pooled birth prevalence of cCMV was 3-fold greater in LMICs (1.42%; 95% CI, 0.97%-2.08%; n = 23 studies) than in HICs (0.48%; 95% CI, 0.40%-0.59%, n = 54 studies). Screening methods with blood samples demonstrated lower rates of cCMV than urine or saliva samples (odds ratio [OR], 0.38; 95% CI, 0.23-0.66). Higher maternal CMV seroprevalence (OR, 1.19; 95% CI, 1.11-1.28), higher population-level HIV prevalence (OR, 1.22; 95% CI, 1.05-1.40), lower socioeconomic status (OR, 3.03; 95% CI, 2.05-4.47), and younger mean maternal age (OR, 0.85; 95% CI, 0.78-0.92, older age was associated with lower rates) were associated with higher rates of cCMV. Conclusions and Relevance: In this meta-analysis, LMICs appeared to incur the most significant infection burden. Lower rates of cCMV were reported by studies using only blood or serum as a screening method.

Pan-African evolution of within- and between-country COVID-19 dynamics.

The coronavirus disease 2019 (COVID-19) pandemic is heterogeneous throughout Africa and threatening millions of lives. Surveillance and short-term modeling forecasts are critical to provide timely information for decisions on control strategies. We created a strategy that helps predict the country-level case occurrences based on cases within or external to a country throughout the entire African continent, parameterized by socioeconomic and geoeconomic variations and the lagged effects of social policy and meteorological history. We observed the effect of the Human Development Index, containment policies, testing capacity, specific humidity, temperature, and landlocked status of countries on the local within-country and external between-country transmission. One-week forecasts of case numbers from the model were driven by the quality of the reported data. Seeking equitable behavioral and social interventions, balanced with coordinated country-specific strategies in infection suppression, should be a continental priority to control the COVID-19 pandemic in Africa.