Background

Vector-borne diseases are a major cause of disease burden in Guayaquil, Ecuador, especially arboviruses spread by Aedes aegypti mosquitoes. Understanding which household characteristics and risk factors lead to higher Ae. aegypti densities and consequent disease risk can help inform and optimize vector control programs.

Methods

Cross-sectional entomological surveys were conducted in Guayaquil between 2013 and 2016, covering household demographics, municipal services, potential breeding containers, presence of Ae. aegypti larvae and pupae, and history of using mosquito control methods. A zero-truncated negative binomial regression model was fitted to data for estimating the household pupal index. An additional model assessed the factors of the most productive breeding sites across all of the households.

Results

Of surveyed households, 610 satisfied inclusion criteria. The final household-level model found that collection of large solid items (e.g., furniture and tires) and rainfall the week of and 2 weeks before collection were negatively correlated with average pupae per container, while bed canopy use, unemployment, container water volume, and the interaction between large solid collection and rainfall 2 weeks before the sampling event were positively correlated. Selection of these variables across other top candidate models with ∆AICc < 1 was robust, with the strongest effects from large solid collection and bed canopy use. The final container-level model explaining the characteristics of breeding sites found that contaminated water is positively correlated with Ae. aegypti pupae counts while breeding sites composed of car parts, furniture, sewerage parts, vases, were all negatively correlated.

Conclusions

Having access to municipal services like bulky item pickup was effective at reducing mosquito proliferation in households. Association of bed canopy use with higher mosquito densities is unexpected, and may be a consequence of large local mosquito populations or due to limited use or effectiveness of other vector control methods. The impact of rainfall on mosquito density is multifaceted, as it may both create new habitat and "wash out" existing habitat. Providing services and social/technical interventions focused on monitoring and eliminating productive breeding sites is important for reducing aquatic-stage mosquito densities in households at risk for Ae. aegypti-transmitted diseases.

Human infection with the Southeast Asian liver fluke Opisthorchis viverrini and liver fluke-associated cholangiocarcinoma cause significant disease burden in Southeast Asia. While there has been considerable work to understand liver fluke pathology and to reduce infection prevalence, there remains a limited understanding of the environmental determinants of parasite transmission dynamics to inform treatment and control programs. A particular setting where targeted control efforts have taken place is the Lawa Lake complex in northeast Thailand. Here, we describe the recent history of host infections, as well as the hydrologic characteristics of this floodplain ecosystem that influence the extent of snail habitat and fish mobility and the transport of human waste and parasite cercariae. Using mathematical modeling, we outline a framework for reconstructing environmental transmission of O. viverrini over the course of the Lawa Project control program from its inception in 2008 until 2016, using locally acquired but fragmentary longitudinal infection data for both humans and environmental hosts. The role of water flow in facilitating movement between snail, fish, human, and reservoir hosts is a particular focus with respect to its relevant scales and its impact on success of interventions. In this setting, we argue that an understanding of the key environmental drivers of disease transmission processes is central to the effectiveness of any environmental intervention.

While efforts to control malaria with available tools have stagnated, and arbovirus outbreaks persist around the globe, the advent of clustered regularly interspaced short palindromic repeat (CRISPR)-based gene editing has provided exciting new opportunities for genetics-based strategies to control these diseases. In one such strategy, called "population replacement", mosquitoes, and other disease vectors are engineered with effector genes that render them unable to transmit pathogens. These effector genes can be linked to "gene drive" systems that can bias inheritance in their favor, providing novel opportunities to replace disease-susceptible vector populations with disease-refractory ones over the course of several generations. While promising for the control of vector-borne diseases on a wide scale, this sets up an evolutionary tug-of-war between the introduced effector genes and the pathogen. Here, we review the disease-refractory genes designed to date to target Plasmodium falciparum malaria transmitted by Anopheles gambiae, and arboviruses transmitted by Aedes aegypti, including dengue serotypes 2 and 3, chikungunya, and Zika viruses. We discuss resistance concerns for these effector genes, and genetic approaches to prevent parasite and viral escape variants. One general approach is to increase the evolutionary hurdle required for the pathogen to evolve resistance by attacking it at multiple sites in its genome and/or multiple stages of development. Another is to reduce the size of the pathogen population by other means, such as with vector control and antimalarial drugs. We discuss lessons learned from the evolution of resistance to antimalarial and antiviral drugs and implications for the management of resistance after its emergence. Finally, we discuss the target product profile for population replacement strategies for vector-borne disease control. This differs between early phase field trials and wide-scale disease control. In the latter case, the demands on effector gene efficacy are great; however, with new possibilities ushered in by CRISPR-based gene editing, and when combined with surveillance, monitoring, and rapid management of pathogen resistance, the odds are increasingly favoring effector genes in the upcoming evolutionary tug-of-war.

Interest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): a significant development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and fundamental improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based split gene drive system intended to drive a disease-refractory gene into a population in a confinable and reversible manner, incorporating time-varying temperature and rainfall data. The simulations also evaluate impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project's CRAN repository. MGDrivE 2 is freely available as an open-source R package on CRAN (https://CRAN.R-project.org/package=MGDrivE2). We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission.

Transmissibility is a significant factor in parasite fitness. The rate and magnitude of parasite transmission affect prevalence and infection intensity in individual hosts and are influenced by environmental factors. In this context, the objectives of this study were: (i) to experimentally assess Opisthorchis viverrini miracidia survival and infectivity over time and across temperatures; and (ii) to combine these experimental results with environmental data to build a key component of a transmission model, identifying seasonal windows of transmission risk in hyper-endemic northeastern Thailand. Five replicates of 50 O. viverrini eggs were randomly distributed and maintained under four temperature conditions (25°C, 30°C, 35°C, 40°C). Microscopic observations were performed on all experimental units over a period of 3months to record miracidia motility and mortality trends. Six infection trials were also conducted to assess infectivity of miracidia over time and across temperatures, using observations of egg hatching success and infection rates. Upon completion of experiments, data were integrated into a transmission model to create a transmission risk index and to simulate seasonal transmission risk. Miracidia survival rate and motility decreased steadily with 50% mortality observed after 2weeks. Hatching and infection success also decreased significantly after 3weeks. Temperatures over 30°C were associated with increased mortality and decreased infectivity. When incorporating local environmental parameters into our model, we observed low transmission risk during the dry season and increasing transmission risk at the onset of the rainy season, culminating with the highest risk in September. We believe that our results provide the first estimates of O. viverrini miracidia survival and transmission potential under variable temperature conditions and suggest that high temperature treatment (>40°C) of fecal waste could be an efficient control strategy.

Importance

A SARS-CoV-2 vaccine was approved for adolescents aged 12 to 15 years on May 10, 2021, with approval for younger age groups following thereafter. The population level impact of the pediatric COVID-19 vaccination program has not yet been established.

Objective

To identify whether California's pediatric COVID-19 immunization program was associated with changes in pediatric COVID-19 incidence and hospitalizations.

Design, setting, and participants

A case series on COVID-19 vaccination including children aged 6 months to 15 years was conducted in California. Data were obtained on COVID-19 cases in California between April 1, 2020, and February 27, 2023.

Exposure

Postvaccination evaluation periods spanned 141 days (June 10 to October 29, 2021) for adolescents aged 12 to 15 years, 199 days (November 29, 2021, to June 17, 2022) for children aged 5 to 11 years, and 225 days (July 17, 2022, to February 27, 2023) for those aged 6 to 59 months. During these periods, statewide vaccine coverage reached 53.5% among adolescents aged 12 to 15 years, 34.8% among children aged 5 to 11 years, and 7.9% among those aged 6 to 59 months.

Main outcomes and measures

Age-stepped implementation of COVID-19 vaccination was used to compare observed county-level incidence and hospitalization rates during periods when each age group became vaccine eligible to counterfactual rates predicted from observations among other age groups. COVID-19 case and hospitalization data were obtained from the California reportable disease surveillance system.

Results

Between April 1, 2020, and February 27, 2023, a total of 3 913 063 pediatric COVID-19 cases and 12 740 hospitalizations were reported in California. Reductions of 146 210 cases (95% prediction interval [PI], 136 056-158 948) were estimated among adolescents aged 12 to 15 years, corresponding to a 37.1% (35.5%-39.1%) reduction from counterfactual predictions. Reductions of 230 134 (200 170-265 149) cases were estimated among children aged 5 to 11 years, corresponding to a 23.7% (20.6%-27.3%) reduction from counterfactual predictions. No evidence of reductions in COVID-19 cases statewide were found among children aged 6 to 59 months (estimated averted cases, -259; 95% PI, -1938 to 1019), although low transmission during the evaluation period may have limited the ability to do so. An estimated 168 hospitalizations (95% PI, 42-324) were averted among children aged 6 to 59 months, corresponding to a 24.4% (95% PI, 6.1%-47.1%) reduction. In meta-analyses, county-level vaccination coverage was associated with averted cases for all age groups. Despite low vaccination coverage, pediatric COVID-19 immunization in California averted 376 085 (95% PI, 348 355-417 328) reported cases and 273 (95% PI, 77-605) hospitalizations among children aged 6 months to 15 years over approximately 4 to 7 months following vaccination availability.

Conclusions and relevance

The findings of this case series analysis of 3 913 063 cases suggest reduced pediatric SARS-CoV-2 transmission following immunization. These results support the use of COVID-19 vaccines to reduce COVID-19 incidence and hospitalization in pediatric populations.

Introduction

Expert knowledge is critical to fight dementia in inequitable regions like Latin American and Caribbean countries (LACs). However, the opinions of aging experts on public policies' accessibility and transmission, stigma, diagnostic manuals, data-sharing platforms, and use of behavioral insights (BIs) are not well known.

Methods

We investigated opinions among health professionals working on aging in LACs (N = 3365) with regression models including expertise-related information (public policies, BI), individual differences (work, age, academic degree), and location.

Results

Experts specified low public policy knowledge (X²  = 41.27, P < .001), high levels of stigma (X²  = 2636.37, P < .001), almost absent BI knowledge (X²  = 56.58, P < .001), and needs for regional diagnostic manuals (X²  = 2893.63, df = 3, P < .001) and data-sharing platforms (X² = 1267.5, df = 3, P < .001). Lack of dementia knowledge was modulated by different factors. An implemented BI-based treatment for a proposed prevention program improved perception across experts.

Discussion

Our findings help to prioritize future potential actions of governmental agencies and non-governmental organizations (NGOs) to improve LACs' dementia knowledge.

Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we reported a survey to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The results show that neuroimaging is the most used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, the region holds a great potential to advance dementia biomarkers research. Considering the unique contributions that LAC could make to this growing field, we highlight the urgent need to expand biomarker research. These insights allowed us to propose an action plan that addresses the recommendations for a biomarker framework recently proposed by regional experts.