Abdominal Ectopic Pregnancy: A Case Report of an Uncommon Complication of Pregnancy Without Prenatal Care.

Ectopic pregnancy (EP) is a life-threatening condition requiring a high clinical suspicion. This diagnosis must be considered in all female patients of reproductive age presenting with abdominal pain or discomfort who may possibly be pregnant. Ectopic pregnancies occur in a small percentage of all pregnancies and are a significant cause of maternal morbidity and mortality. Abdominal ectopic pregnancy (AEP) is a rare and potentially fatal form of ectopic pregnancy where the implantation occurs in the abdominal cavity. We present the following case of a 23-year-old female who was transferred following an initial workup for abdominal pain and subsequently found to have an abdominal ectopic pregnancy at 37 weeks gestation. After transferring to our emergency department, the patient continued to have abdominal pain and her presenting FAST exam was positive for free fluid concerning for active hemorrhage and hematoma. Her clinical presentation was consistent with ruptured abdominal ectopic pregnancy, and she was taken to the operating room for emergent exploratory laparotomy and delivery. Her clinical course was complicated by adherent placenta and re-bleeding with significant hemoperitoneum requiring re-entry laparotomy and transfusion. We present the details of this case along with the diagnostic imaging and management of the rarely seen and life-threatening condition of secondary abdominal ectopic pregnancy (AEP).

Using priorities between human and livestock bacterial antimicrobial resistance (AMR) to identify data gaps in livestock AMR surveillance.

BACKGROUND: Bacterial antimicrobial resistance (AMR) is a global threat to both humans and livestock. Despite this, there is limited global consensus on data-informed, priority areas for intervention in both sectors. We compare current livestock AMR data collection efforts with other variables pertinent to human and livestock AMR to identify critical data gaps and mutual priorities. METHODS: We globally synthesized livestock AMR data from open-source surveillance reports and point prevalence surveys stratified for six pathogens (Escherichia coli, Staphylococcus aureus, non-typhoidal Salmonella, Campylobacter spp., Enterococcus faecalis, Enterococcus faecium) and eleven antimicrobial classes important in human and veterinary use, published between 2000 and 2020. We also included all livestock species represented in the data: cattle, chickens, pigs, sheep, turkeys, ducks, horses, buffaloes, and goats. We compared this data with intended priorities calculated from: disability-adjusted life years (DALYs), livestock antimicrobial usage (AMU), livestock biomass, and a global correlation exercise between livestock and human proportion of resistant isolates. RESULTS: Resistance to fluoroquinolones and macrolides in Staphylococcus aureus were identified as priorities in many countries but, less than 10% of these reported livestock AMR data. Resistance data for Escherichia coli specific to cattle, chickens, and pigs, which we prioritized, were also well collected. AMR data collection on non-typhoidal Salmonella and other livestock species were often not prioritized. Of 232 categories prioritized by at least one country, data were only collected for 48% (n = 112). CONCLUSIONS: The lack of livestock AMR data globally for broad resistance in Staphylococcus aureus could underplay their zoonotic threat. Countries can bolster livestock AMR data collection, reporting, and intervention setting for Staphylococcus aureus as done for Escherichia coli. This framework can provide guidance on areas to strengthen AMR surveillance and decision-making for humans and livestock, and if done routinely, can adapt to resistance trends and priorities.

Human movement and environmental barriers shape the emergence of dengue.

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

Estimating vaccine efficacy during open-label follow-up of COVID-19 vaccine trials based on population-level surveillance data.

While rapid development and roll out of COVID-19 vaccines is necessary in a pandemic, the process limits the ability of clinical trials to assess longer-term vaccine efficacy. We leveraged COVID-19 surveillance data in the U.S. to evaluate vaccine efficacy in U.S. Government-funded COVID-19 vaccine efficacy trials with a three-step estimation process. First, we used a compartmental epidemiological model informed by county-level surveillance data, a "population model", to estimate SARS-CoV-2 incidence among the unvaccinated. Second, a "cohort model" was used to adjust the population SARS-CoV-2 incidence to the vaccine trial cohort, taking into account individual participant characteristics and the difference between SARS-CoV-2 infection and COVID-19 disease. Third, we fit a regression model estimating the offset between the cohort-model-based COVID-19 incidence in the unvaccinated with the placebo-group COVID-19 incidence in the trial during blinded follow-up. Counterfactual placebo COVID-19 incidence was estimated during open-label follow-up by adjusting the cohort-model-based incidence rate by the estimated offset. Vaccine efficacy during open-label follow-up was estimated by contrasting the vaccine group COVID-19 incidence with the counterfactual placebo COVID-19 incidence. We documented good performance of the methodology in a simulation study. We also applied the methodology to estimate vaccine efficacy for the two-dose AZD1222 COVID-19 vaccine using data from the phase 3 U.S. trial (ClinicalTrials.gov # NCT04516746). We estimated AZD1222 vaccine efficacy of 59.1% (95% uncertainty interval (UI): 40.4%-74.3%) in April, 2021 (mean 106 days post-second dose), which reduced to 35.7% (95% UI: 15.0%-51.7%) in July, 2021 (mean 198 days post-second-dose). We developed and evaluated a methodology for estimating longer-term vaccine efficacy. This methodology could be applied to estimating counterfactual placebo incidence for future placebo-controlled vaccine efficacy trials of emerging pathogens with early termination of blinded follow-up, to active-controlled or uncontrolled COVID-19 vaccine efficacy trials, and to other clinical endpoints influenced by vaccination.

A review of emerging health threats from zoonotic New World mammarenaviruses.

Despite repeated spillover transmission and their potential to cause significant morbidity and mortality in human hosts, the New World mammarenaviruses remain largely understudied. These viruses are endemic to South America, with animal reservoir hosts covering large geographic areas and whose transmission ecology and spillover potential are driven in part by land use change and agriculture that put humans in regular contact with zoonotic hosts.We compiled published studies about Guanarito virus, Junin virus, Machupo virus, Chapare virus, Sabia virus, and Lymphocytic Choriomeningitis virus to review the state of knowledge about the viral hemorrhagic fevers caused by New World mammarenaviruses. We summarize what is known about rodent reservoirs, the conditions of spillover transmission for each of these pathogens, and the characteristics of human populations at greatest risk for hemorrhagic fever diseases. We also review the implications of repeated outbreaks and biosecurity concerns where these diseases are endemic, and steps that countries can take to strengthen surveillance and increase capacity of local healthcare systems. While there are unique risks posed by each of these six viruses, their ecological and epidemiological similarities suggest common steps to mitigate spillover transmission and better contain future outbreaks.

Livestock, pathogens, vectors, and their environment: A causal inference-based approach to estimating the pathway-specific effect of livestock on human African trypanosomiasis risk.

Livestock are important reservoirs for many zoonotic diseases, however the effects of livestock on human and environmental health extend well beyond direct disease transmission. In this retrospective ecological cohort study we use pre-existing data and the parametric g-formula, which imputes potential outcomes to quantify mediation, to estimate three hypothesized mechanisms by which livestock can influence human African trypanosomiasis (HAT) risk: the reservoir effect, where infected cattle and pigs are a source of infection to humans; the zooprophylactic effect, where preference for livestock hosts exhibited by the tsetse fly vector of HAT means that their presence protects humans from infection; and the environmental change effect, where livestock keeping activities modify the environment in such a way that habitat suitability for tsetse flies, and in turn human infection risk, is reduced. We conducted this study in four high burden countries: at the point level in Uganda, Malawi, and Democratic Republic of Congo (DRC), and at the county level in South Sudan. Our results indicate cattle and pigs play a reservoir role for the rhodesiense form (rHAT) in Uganda (rate ratio (RR) 1.68, 95% CI 0.84, 2.82 for cattle; RR 2.16, 95% CI 1.18, 3.05 for pigs), however zooprophylaxis outweighs this effect for rHAT in Malawi (RR 0.85, 95% CI 0.68, 1.00 for cattle, RR 0.38, 95% CI 0.21, 0.69 for pigs). For the gambiense form (gHAT) we found evidence that pigs may be a competent reservoir (RR 1.15, 95% CI 0.92, 1.72 in Uganda; RR 1.25, 95% CI 1.11, 1.42 in DRC). Statistical significance was reached for rHAT in Malawi (pigs and cattle) and Uganda (pigs only) and for gHAT in DRC (pigs and cattle). We did not find compelling evidence of an environmental change effect (all effect sizes close to 1).

Animal sources of antimicrobial-resistant bacterial infections in humans: a systematic review.

Bacterial antimicrobial resistance (AMR) is among the leading global health challenges of the century. Animals and their products are known contributors to the human AMR burden, but the extent of this contribution is not clear. This systematic literature review aimed to identify studies investigating the direct impact of animal sources, defined as livestock, aquaculture, pets, and animal-based food, on human AMR. We searched four scientific databases and identified 31 relevant publications, including 12 risk assessments, 16 source attribution studies, and three other studies. Most studies were published between 2012 and 2022, and most came from Europe and North America, but we also identified five articles from South and South-East Asia. The studies differed in their methodologies, conceptual approaches (bottom-up, top-down, and complex), definitions of the AMR hazard and outcome, the number and type of sources they addressed, and the outcome measures they reported. The most frequently addressed animal source was chicken, followed by cattle and pigs. Most studies investigated bacteria-resistance combinations. Overall, studies on the direct contribution of animal sources of AMR are rare but increasing. More recent publications tailor their methodologies increasingly towards the AMR hazard as a whole, providing grounds for future research to build on.

The global burden of neglected zoonotic diseases: Current state of evidence.

The majority of emerging infectious diseases are zoonoses, most of which are classified as "neglected". By affecting both humans and animals, zoonoses pose a dual burden. The disability-adjusted life year (DALY) metric quantifies human health burden since it combines mortality and morbidity. This review aims to describe and analyze the current state of evidence on neglected zoonotic diseases (NZDs) burden and start a discussion on the current understanding of the global burden of NZDs. We identified 26 priority NZDs through consulting three international repositories for national prioritization exercises. A systematic review of global and national burden of disease (BoD) studies was conducted using pre-selected databases. Data on diseases, location and DALYs were extracted for each eligible study. A total of 1887 records were screened, resulting in 74 eligible studies. The highest number of BoD was found for non-typhoidal salmonellosis (23), whereas no estimates were found for West Nile, Marburg and Lassa fever. Geographically, the highest number of studies was performed in the Netherlands (11), China (5) and Iran (4). The number of BoD retrieved mismatched the perceived importance in national prioritization exercises. For example, anthrax was considered a priority NZD in 65 countries; however, only one national study estimating BoD was retrieved. By summing the available global estimates, the selected NZDs caused at least 21 million DALYs per year, a similar order of magnitude to (but less than) the burden due to foodborne disease (included in the Foodborne Disease Burden Epidemiology Reference Group). The global burden of disease landscape of NZDs remains scattered. There are several priority NZDs for which no burden estimates exist, and the number of BoD studies does not reflect national disease priorities. To have complete and consistent estimates of the global burden of NZDs, these diseases should be integrated in larger global burden of disease initiatives.