Local and regional dynamics of chikungunya virus transmission in Colombia: the role of mismatched spatial heterogeneity.

BACKGROUND: Mathematical models of transmission dynamics are routinely fitted to epidemiological time series, which must inevitably be aggregated at some spatial scale. Weekly case reports of chikungunya have been made available nationally for numerous countries in the Western Hemisphere since late 2013, and numerous models have made use of this data set for forecasting and inferential purposes. Motivated by an abundance of literature suggesting that the transmission of this mosquito-borne pathogen is localized at scales much finer than nationally, we fitted models at three different spatial scales to weekly case reports from Colombia to explore limitations of analyses of nationally aggregated time series data. METHODS: We adapted the recently developed Disease Transmission Kernel (DTK)-Dengue model for modeling chikungunya virus (CHIKV) transmission, given the numerous similarities of these viruses vectored by a common mosquito vector. We fitted versions of this model specified at different spatial scales to weekly case reports aggregated at different spatial scales: (1) single-patch national model fitted to national data; (2) single-patch departmental models fitted to departmental data; and (3) multi-patch departmental models fitted to departmental data, where the multiple patches refer to municipalities within a department. We compared the consistency of simulations from fitted models with empirical data. RESULTS: We found that model consistency with epidemic dynamics improved with increasing spatial granularity of the model. Specifically, the sum of single-patch departmental model fits better captured national-level temporal patterns than did a single-patch national model. Likewise, multi-patch departmental model fits better captured department-level temporal patterns than did single-patch departmental model fits. Furthermore, inferences about municipal-level incidence based on multi-patch departmental models fitted to department-level data were positively correlated with municipal-level data that were withheld from model fitting. CONCLUSIONS: Our model performed better when posed at finer spatial scales, due to better matching between human populations with locally relevant risk. Confronting spatially aggregated models with spatially aggregated data imposes a serious structural constraint on model behavior by averaging over epidemiologically meaningful spatial variation in drivers of transmission, impairing the ability of models to reproduce empirical patterns.

The future of a partially effective HIV vaccine: assessing limitations at the population level.

OBJECTIVES: Mathematical models have unanimously predicted that a first-generation HIV vaccine would be useful and cost-effective to roll out, but that its overall impact would be insufficient to reverse the epidemic. Here, we explore what factors contribute most to limiting the impact of such a vaccine. METHODS: Ranging from a theoretical ideal to a more realistic regimen, mirroring the one used in the currently ongoing trial in South Africa (HVTN 702), we model a nested hierarchy of vaccine attributes such as speed of scale-up, efficacy, durability, and return rates for booster doses. RESULTS: The predominant reasons leading to a substantial loss of vaccine impact on the HIV epidemic are the time required to scale up mass vaccination, limited durability, and waning of efficacy. CONCLUSIONS: A first-generation partially effective vaccine would primarily serve as an intermediate milestone, furnishing correlates of immunity and platforms that could serve to accelerate future development of a highly effective, durable, and scalable next-generation vaccine capable of reversing the HIV epidemic.

Biocompatible near-infrared quantum dots delivered to the skin by microneedle patches record vaccination.

Accurate medical recordkeeping is a major challenge in many low-resource settings where well-maintained centralized databases do not exist, contributing to 1.5 million vaccine-preventable deaths annually. Here, we present an approach to encode medical history on a patient using the spatial distribution of biocompatible, near-infrared quantum dots (NIR QDs) in the dermis. QDs are invisible to the naked eye yet detectable when exposed to NIR light. QDs with a copper indium selenide core and aluminum-doped zinc sulfide shell were tuned to emit in the NIR spectrum by controlling stoichiometry and shelling time. The formulation showing the greatest resistance to photobleaching after simulated sunlight exposure (5-year equivalence) through pigmented human skin was encapsulated in microparticles for use in vivo. In parallel, microneedle geometry was optimized in silico and validated ex vivo using porcine and synthetic human skin. QD-containing microparticles were then embedded in dissolvable microneedles and administered to rats with or without a vaccine. Longitudinal in vivo imaging using a smartphone adapted to detect NIR light demonstrated that microneedle-delivered QD patterns remained bright and could be accurately identified using a machine learning algorithm 9 months after application. In addition, codelivery with inactivated poliovirus vaccine produced neutralizing antibody titers above the threshold considered protective. These findings suggest that intradermal QDs can be used to reliably encode information and can be delivered with a vaccine, which may be particularly valuable in the developing world and open up new avenues for decentralized data storage and biosensing.

A heat-stable microparticle platform for oral micronutrient delivery.

Micronutrient deficiencies affect up to 2 billion people and are the leading cause of cognitive and physical disorders in the developing world. Food fortification is effective in treating micronutrient deficiencies; however, its global implementation has been limited by technical challenges in maintaining micronutrient stability during cooking and storage. We hypothesized that polymer-based encapsulation could address this and facilitate micronutrient absorption. We identified poly(butylmethacrylate-co-(2-dimethylaminoethyl)methacrylate-co-methylmethacrylate) (1:2:1) (BMC) as a material with proven safety, offering stability in boiling water, rapid dissolution in gastric acid, and the ability to encapsulate distinct micronutrients. We encapsulated 11 micronutrients (iron; iodine; zinc; and vitamins A, B2, niacin, biotin, folic acid, B12, C, and D) and co-encapsulated up to 4 micronutrients. Encapsulation improved micronutrient stability against heat, light, moisture, and oxidation. Rodent studies confirmed rapid micronutrient release in the stomach and intestinal absorption. Bioavailability of iron from microparticles, compared to free iron, was lower in an initial human study. An organotypic human intestinal model revealed that increased iron loading and decreased polymer content would improve absorption. Using process development approaches capable of kilogram-scale synthesis, we increased iron loading more than 30-fold. Scaled batches tested in a follow-up human study exhibited up to 89% relative iron bioavailability compared to free iron. Collectively, these studies describe a broad approach for clinical translation of a heat-stable ingestible micronutrient delivery platform with the potential to improve micronutrient deficiency in the developing world. These approaches could potentially be applied toward clinical translation of other materials, such as natural polymers, for encapsulation and oral delivery of micronutrients.

Pathway to Deployment of Gene Drive Mosquitoes as a Potential Biocontrol Tool for Elimination of Malaria in Sub-Saharan Africa: Recommendations of a Scientific Working Group†.

Gene drive technology offers the promise for a high-impact, cost-effective, and durable method to control malaria transmission that would make a significant contribution to elimination. Gene drive systems, such as those based on clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated protein, have the potential to spread beneficial traits through interbreeding populations of malaria mosquitoes. However, the characteristics of this technology have raised concerns that necessitate careful consideration of the product development pathway. A multidisciplinary working group considered the implications of low-threshold gene drive systems on the development pathway described in the World Health Organization Guidance Framework for testing genetically modified (GM) mosquitoes, focusing on reduction of malaria transmission by Anopheles gambiae s.l. mosquitoes in Africa as a case study. The group developed recommendations for the safe and ethical testing of gene drive mosquitoes, drawing on prior experience with other vector control tools, GM organisms, and biocontrol agents. These recommendations are organized according to a testing plan that seeks to maximize safety by incrementally increasing the degree of human and environmental exposure to the investigational product. As with biocontrol agents, emphasis is placed on safety evaluation at the end of physically confined laboratory testing as a major decision point for whether to enter field testing. Progression through the testing pathway is based on fulfillment of safety and efficacy criteria, and is subject to regulatory and ethical approvals, as well as social acceptance. The working group identified several resources that were considered important to support responsible field testing of gene drive mosquitoes.

Implementation and applications of EMOD, an individual-based multi-disease modeling platform.

Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach developed with formal software support. The epidemiological modeling software, EMOD, has undergone a decade of software development. It is structured so that a majority of code is shared across disease modeling including malaria, HIV, tuberculosis, dengue, polio and typhoid. In additional to implementation efficiency, the sharing increases code usage and testing. The freely available codebase also includes hundreds of regression tests, scientific feature tests and component tests to help verify functionality and avoid inadvertent changes to functionality during future development. Here we describe the levels of detail, flexible configurability and modularity enabled by EMOD and the role of software development principles and processes in its development.