Repeat mediated excision of gene drive elements for restoring wild-type populations.

Here, we demonstrate that single strand annealing (SSA) can be co-opted for the precise autocatalytic excision of a drive element. We have termed this technology Repeat Mediated Excision of a Drive Element (ReMEDE). By engineering direct repeats flanking the drive allele and inducing a double-strand DNA break (DSB) at a second endonuclease target site within the allele, we increased the utilization of SSA repair.

Mechanistic Models of Influenza Transmission in Commercial Swine Populations: A Systematic Review.

Influenza in commercial swine populations leads to reduced gain in fattening pigs and reproductive issues in sows. This literature review aims to analyze the contributions of mathematical modeling in understanding influenza transmission and control among domestic swine. Twenty-two full-text research articles from seven databases were reviewed, categorized into swine-only ( = 13), swine-avian ( = 3), and swine-human models ( = 6).

Global risk of dengue outbreaks and the impact of El Niño events.

Background: Dengue fever is an arboviral disease caused by the dengue virus (DENV). Its geographical distribution and health burden have been steadily increasing through tropical and subtropical climates in recent decades.

Methods: We developed a temperature- and precipitation-dependent mechanistic model for the global risk of dengue fever outbreaks using the basic reproduction number (R) as the metric of disease transmission risk.

The Reproduction Number of Swine Viral Respiratory Diseases: A Systematic Review.

Diseases in the swine industry can cause significant economic and health impacts. This review examines R estimates for respiratory diseases in pigs, assessing variations and comparing transmission risks within and between farms. A literature search of three databases aggregated peer-reviewed research articles on swine viral respiratory diseases' R values.

Analyzing the use of non-pharmaceutical personal protective measures through self-interest and social optimum for the control of an emerging disease.

Non-pharmaceutical personal protective (NPP) measures such as face masks use, and hand and respiratory hygiene can be effective measures for mitigating the spread of aerosol/airborne diseases, such as COVID-19, in the absence of vaccination or treatment. However, the usage of such measures is constrained by their inherent perceived cost and effectiveness for reducing transmission risk. To understand the complex interaction of disease dynamics and individuals decision whether to adopt NPP or not, we incorporate evolutionary game theory into an epidemic model such as COVID-19.

Improved Assessment of Community Infection Through Data Resampling Method.

Background: The conventional diagnostic for infection is stool microscopy with the Kato-Katz (KK) technique to detect eggs. Its outcomes are highly variable on a day-to-day basis and may lead to biased estimates of community infection used to inform public health programs. Our goal is to develop a resampling method that leverages data from a large-scale randomized trial to accurately predict community infection.

Repeat mediated excision of gene drive elements for restoring wild-type populations.

We demonstrate here that single strand annealing (SSA) repair can be co-opted for the precise autocatalytic excision of a drive element. Although SSA is not the predominant form of DNA repair in eukaryotic organisms, we increased the likelihood of its use by engineering direct repeats at sites flanking the drive allele, and then introducing a double-strand DNA break (DSB) at a second endonuclease target site encoded within the drive allele. We have termed this technology Repeat Mediated Excision of a Drive Element (ReMEDE).

Expansions to the MGDrivE suite for simulating the efficacy of novel gene-drive constructs in the control of mosquito-borne diseases.

Objective: The MGDrivE (MGDrivE 1 and MGDrivE 2) modeling framework provides a flexible and expansive environment for testing the efficacy of novel gene-drive constructs for the control of mosquito-borne diseases. However, the existing model framework did not previously support several features necessary to simulate some types of intervention strategies. Namely, current MGDrivE versions do not permit modeling of small molecule inducible systems for controlling gene expression in gene drive designs or the inheritance patterns of self-eliminating gene drive mechanisms.

Effectiveness of Systemic Insecticide Dog Treatment for the Control of Chagas Disease in the Tropics.

Chagas disease, caused by and transmitted by triatomines, can lead to severe cardiac issues and mortality in many mammals. Recent studies have shown that systemic insecticide treatment of dogs is highly effective in killing triatomines. Here, we assessed the impact of dog treatment on transmission.

A Scoping Review of Mathematical Models Used to Investigate the Role of Dogs in Chagas Disease Transmission.

Chagas disease is a zoonotic vector-borne disease caused by the parasite , which affects a variety of mammalian species across the Americas, including humans and dogs. Mathematical modeling has been widely used to investigate the transmission dynamics and control of vector-borne diseases. We performed a scoping review of mathematical models that investigated the role of dogs in transmission.

Effectiveness of fluralaner treatment regimens for the control of canine Chagas disease: A mathematical modeling study.

Background: Canine Chagas disease is caused by the protozoan parasite Trypanosoma cruzi and transmitted by insect triatomine vectors known as kissing bugs. The agent can cause cardiac damage and long-term heart disease and death in humans, dogs, and other mammals. In laboratory settings, treatment of dogs with systemic insecticides has been shown to be highly efficacious at killing triatomines that feed on treated dogs.

Evaluation of the US Definitions for Coronavirus Disease 2019 Community Risk Levels.

The US Centers for Disease Control and Prevention (CDC) defines a county metric of coronavirus disease 2019 (COVID-19) community levels to inform public health measures. We find that the COVID-19 community levels vary frequently over time, which may not be optimal for decision making. Alternative metric formulations that do not compromise predictive ability are shown to reduce variability.

Calibrating COVID-19 community transmission risk levels to reflect infection prevalence.

Many organizations, including the US Centers for Disease Control and Prevention, have developed risk indexes to help determine community transmission levels for the ongoing COVID-19 pandemic. These risk indexes are largely based on newly reported cases and percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests, which are well-established as biased estimates of COVID-19 transmission. However, transmission risk indexes should accurately and precisely communicate community risks to decision-makers and the public.

Using test positivity and reported case rates to estimate state-level COVID-19 prevalence and seroprevalence in the United States.

Accurate estimates of infection prevalence and seroprevalence are essential for evaluating and informing public health responses and vaccination coverage needed to address the ongoing spread of COVID-19 in each United States (U.S.) state.

Forecasting influenza-like illness trends in Cameroon using Google Search Data.

Although acute respiratory infections are a leading cause of mortality in sub-Saharan Africa, surveillance of diseases such as influenza is mostly neglected. Evaluating the usefulness of influenza-like illness (ILI) surveillance systems and developing approaches for forecasting future trends is important for pandemic preparedness. We applied and compared a range of robust statistical and machine learning models including random forest (RF) regression, support vector machines (SVM) regression, multivariable linear regression and ARIMA models to forecast 2012 to 2018 trends of reported ILI cases in Cameroon, using Google searches for influenza symptoms, treatments, natural or traditional remedies as well as, infectious diseases with a high burden (i.

Optimizing antiviral treatment for seasonal influenza in the USA: a mathematical modeling analysis.

Background: Seasonal influenza remains a major cause of morbidity and mortality in the USA. Despite the US Centers for Disease Control and Prevention recommendation promoting the early antiviral treatment of high-risk patients, treatment coverage remains low.

Methods: To evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the USA, we developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior.

Using Test Positivity and Reported Case Rates to Estimate State-Level COVID-19 Prevalence and Seroprevalence in the United States.

Unlabelled: Accurate estimates of infection prevalence and seroprevalence are essential for evaluating and informing public health responses needed to address the ongoing spread of COVID-19 in the United States. A data-driven Bayesian single parameter semi-empirical model was developed and used to evaluate state-level prevalence and seroprevalence of COVID-19 using daily reported cases and test positivity ratios. COVID-19 prevalence is well-approximated by the of the positivity rate and the reported case rate.

State-level needs for social distancing and contact tracing to contain COVID-19 in the United States.

Starting in mid-May 2020, many US states began relaxing social-distancing measures that were put in place to mitigate the spread of COVID-19. To evaluate the impact of relaxation of restrictions on COVID-19 dynamics and control, we developed a transmission dynamic model and calibrated it to US state-level COVID-19 cases and deaths. We used this model to evaluate the impact of social distancing, testing and contact tracing on the COVID-19 epidemic in each state.

State-level needs for social distancing and contact tracing to contain COVID-19 in the United States.

Starting in mid-May 2020, many US states began relaxing social distancing measures that were put in place to mitigate the spread of COVID-19. To evaluate the impact of relaxation of restrictions on COVID-19 dynamics and control, we developed a transmission dynamic model and calibrated it to US state-level COVID-19 cases and deaths. We used this model to evaluate the impact of social distancing, testing and contact tracing on the COVID-19 epidemic in each state.

High Rate of Non-Human Feeding by Reduces Zika Virus Transmission in South Texas.

Mosquito-borne viruses are emerging or re-emerging globally, afflicting millions of people around the world. , the yellow fever mosquito, is the principal vector of dengue, Zika, and chikungunya viruses, and has well-established populations across tropical and subtropical urban areas of the Americas, including the southern United States. While intense arboviral epidemics have occurred in Mexico and further south in the Americas, local transmission in the United States has been minimal.

Spatio-temporal dynamics of measles outbreaks in Cameroon.

Purpose: In 2012, Cameroon experienced a large measles outbreak of over 14,000 cases. To determine the spatio-temporal dynamics of measles transmission in Cameroon, we analyzed weekly case data collected by the Ministry of Health.

Methods: We compared several multivariate time-series models of population movement to characterize the spatial spread of measles in Cameroon.

The impact of vector migration on the effectiveness of strategies to control gambiense human African trypanosomiasis.

Background: Several modeling studies have been undertaken to assess the feasibility of the WHO goal of eliminating gambiense human African trypanosomiasis (g-HAT) by 2030. However, these studies have generally overlooked the effect of vector migration on disease transmission and control. Here, we evaluated the impact of vector migration on the feasibility of interrupting transmission in different g-HAT foci.

The exacerbation of Ebola outbreaks by conflict in the Democratic Republic of the Congo.

The interplay between civil unrest and disease transmission is not well understood. Violence targeting healthcare workers and Ebola treatment centers in the Democratic Republic of the Congo (DRC) has been thwarting the case isolation, treatment, and vaccination efforts. The extent to which conflict impedes public health response and contributes to incidence has not previously been evaluated.

Global Risk and Elimination of Yellow Fever Epidemics.

Background: Yellow fever (YF) is a vector-borne viral hemorrhagic disease endemic in Africa and Latin America. In 2016, the World Health Organization (WHO) developed the Eliminate YF Epidemics strategy aiming at eliminating YF epidemics by 2026.

Methods: We developed a spatiotemporal model of YF, accounting for the impact of temperature, vector distribution, and socioeconomic factors on disease transmission.