MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito populations.

Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entails the need to distribute mosquito traps efficiently such that an allele of interest is detected as quickly as possible-ideally when remediation is still viable. Additionally, insecticide-based tools such as bednets are compromised by insecticide-resistance alleles for which there is also a need to detect as quickly as possible. To this end, we present MGSurvE (Mosquito Gene SurveillancE): a computational framework that optimizes trap placement for genetic surveillance of mosquito populations such that the time to detection of an allele of interest is minimized. A key strength of MGSurvE is that it allows important biological features of mosquitoes and the landscapes they inhabit to be accounted for, namely: i) resources required by mosquitoes (e.g., food sources and aquatic breeding sites) can be explicitly distributed through a landscape, ii) movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female) and resource attractiveness, and iii) traps may differ in their attractiveness profile. Example MGSurvE analyses are presented to demonstrate optimal trap placement for: i) an Aedes aegypti population in a suburban landscape in Queensland, Australia, and ii) an Anopheles gambiae population on the island of São Tomé, São Tomé and Príncipe. Further documentation and use examples are provided in project's documentation. MGSurvE is intended as a resource for both field and computational researchers interested in mosquito gene surveillance.

Mapping HIV prevalence in sub-Saharan Africa between 2000 and 2017.

HIV/AIDS is a leading cause of disease burden in sub-Saharan Africa. Existing evidence has demonstrated that there is substantial local variation in the prevalence of HIV; however, subnational variation has not been investigated at a high spatial resolution across the continent. Here we explore within-country variation at a 5 × 5-km resolution in sub-Saharan Africa by estimating the prevalence of HIV among adults (aged 15-49 years) and the corresponding number of people living with HIV from 2000 to 2017. Our analysis reveals substantial within-country variation in the prevalence of HIV throughout sub-Saharan Africa and local differences in both the direction and rate of change in HIV prevalence between 2000 and 2017, highlighting the degree to which important local differences are masked when examining trends at the country level. These fine-scale estimates of HIV prevalence across space and time provide an important tool for precisely targeting the interventions that are necessary to bringing HIV infections under control in sub-Saharan Africa.

Spatial dynamics of malaria transmission.

The Ross-Macdonald model has exerted enormous influence over the study of malaria transmission dynamics and control, but it lacked features to describe parasite dispersal, travel, and other important aspects of heterogeneous transmission. Here, we present a patch-based differential equation modeling framework that extends the Ross-Macdonald model with sufficient skill and complexity to support planning, monitoring and evaluation for Plasmodium falciparum malaria control. We designed a generic interface for building structured, spatial models of malaria transmission based on a new algorithm for mosquito blood feeding. We developed new algorithms to simulate adult mosquito demography, dispersal, and egg laying in response to resource availability. The core dynamical components describing mosquito ecology and malaria transmission were decomposed, redesigned and reassembled into a modular framework. Structural elements in the framework-human population strata, patches, and aquatic habitats-interact through a flexible design that facilitates construction of ensembles of models with scalable complexity to support robust analytics for malaria policy and adaptive malaria control. We propose updated definitions for the human biting rate and entomological inoculation rates. We present new formulas to describe parasite dispersal and spatial dynamics under steady state conditions, including the human biting rates, parasite dispersal, the "vectorial capacity matrix," a human transmitting capacity distribution matrix, and threshold conditions. An [Formula: see text] package that implements the framework, solves the differential equations, and computes spatial metrics for models developed in this framework has been developed. Development of the model and metrics have focused on malaria, but since the framework is modular, the same ideas and software can be applied to other mosquito-borne pathogen systems.

Mapping child growth failure in Africa between 2000 and 2015.

Insufficient growth during childhood is associated with poor health outcomes and an increased risk of death. Between 2000 and 2015, nearly all African countries demonstrated improvements for children under 5 years old for stunting, wasting, and underweight, the core components of child growth failure. Here we show that striking subnational heterogeneity in levels and trends of child growth remains. If current rates of progress are sustained, many areas of Africa will meet the World Health Organization Global Targets 2025 to improve maternal, infant and young child nutrition, but high levels of growth failure will persist across the Sahel. At these rates, much, if not all of the continent will fail to meet the Sustainable Development Goal target-to end malnutrition by 2030. Geospatial estimates of child growth failure provide a baseline for measuring progress as well as a precision public health platform to target interventions to those populations with the greatest need, in order to reduce health disparities and accelerate progress.

Comparing metapopulation dynamics of infectious diseases under different models of human movement.

Newly available datasets present exciting opportunities to investigate how human population movement contributes to the spread of infectious diseases across large geographical distances. It is now possible to construct realistic models of infectious disease dynamics for the purposes of understanding global-scale epidemics. Nevertheless, a remaining unanswered question is how best to leverage the new data to parameterize models of movement, and whether one's choice of movement model impacts modeled disease outcomes. We adapt three well-studied models of infectious disease dynamics, the susceptible-infected-recovered model, the susceptible-infected-susceptible model, and the Ross-Macdonald model, to incorporate either of two candidate movement models. We describe the effect that the choice of movement model has on each disease model's results, finding that in all cases, there are parameter regimes where choosing one movement model instead of another has a profound impact on epidemiological outcomes. We further demonstrate the importance of choosing an appropriate movement model using the applied case of malaria transmission and importation on Bioko Island, Equatorial Guinea, finding that one model produces intelligible predictions of R0, whereas the other produces nonsensical results.

Computed Tomography Coronary Angiography on a Detector-Based Spectral Computed Tomography Platform: Evaluation of Patients With Coronary Artery Disease Reporting and Data System Score of 3 and Higher.

PURPOSE: Computed tomography (CT) coronary angiography performed on a detector-based spectral scanner helps more closely approximate severity of stenosis with nuclear medicine and cardiac catheterization tests compared with single-energy CT (SECT) in patients with an original CAD-RADS score of 3 and higher. METHODS: This retrospective trial was conducted between January 2017 and December 2019 and included 52 patients with a CAD-RADS score of 3 and higher. Two reading sessions were performed 6 weeks apart. The first reading session was performed using only conventional images and the second reading session was performed using spectral results. Detector-based spectral CT CAD-RADS scores were compared with cardiac stress test and/or cardiac catheterization results for final characterization of stenosis in 41 segments from 32 patients. The mean CAD-RADS score was calculated for both the conventional images and spectral images. RESULTS: The CAD-RADS score for SECT and the score for spectral CT for the 41 segments were compared. Available associated stress test and/or cardiac catheterization results were also compared with CAD-RADS scores. In 51% (21/41), a diagnosis concordant with best practices results was achieved with the help of spectral CT results. A mean CAD-RADS score of 3.56 was obtained using spectral results, compared with 3.93 using conventional images. A 2-tailed paired t test determined the difference to be significant with a P value of 0.007. CONCLUSIONS: Computed tomography coronary angiography is feasible on a detector-based spectral CT scanner and can improve diagnostic confidence over SECT angiography in patients with an original CAD-RADS score of 3 and higher.

Infection age as a predictor of epidemiological metrics for malaria.

BACKGROUND: Accurate estimation of the burden of Plasmodium falciparum is essential for strategic planning for control and elimination. Due in part to the extreme heterogeneity in malaria exposure, immunity, other causes of disease, direct measurements of fever and disease attributable to malaria can be difficult. This can make a comparison of epidemiological metrics both within and between populations hard to interpret. An essential part of untangling this is an understanding of the complex time-course of malaria infections. METHODS: Historic data from malariatherapy infections, in which individuals were intentionally infected with malaria parasites, were reexamined in aggregate. In this analysis, the age of each infection was examined as a potential predictor describing aggregate patterns across all infections. A series of piecewise linear and generalized linear regressions were performed to highlight the infection age-dependent patterns in both parasitaemia and gametocytaemia, and from parasitaemia and gametocytaemia to fever and transmission probabilities, respectively. RESULTS: The observed duration of untreated patent infection was 130 days. As infections progressed, the fraction of infections subpatent by microscopy was seen to increase steadily. The time-averaged malaria infections had three distinct phases in parasitaemia: a growth phase for the first 6 days of patency, a rapid decline from day 6 to day 18, and a slowly declining chronic phase for the remaining duration of the infection. During the growth phase, parasite densities increased sharply to a peak. Densities sharply decline for a short period of time after the peak. During the chronic phase, infections declined steadily as infections age. gametocytaemia was strongly correlated with lagged asexual parasitaemia. Fever rates and transmission efficiency were strongly correlated with parasitaemia and gametocytaemia. The comparison between raw data and prediction from the age of infection has good qualitative agreement across all quantities of interest for predicting averaged effects. CONCLUSION: The age of infection was established as a potentially useful covariate for malaria epidemiology. Infection age can be estimated given a history of exposure, and accounting for exposure history may potentially provide a new way to estimate malaria-attributable fever rates, transmission efficiency, and patent fraction in immunologically naïve individuals such as children and people in low-transmission regions. These data were collected from American adults with neurosyphilis, so there are reasons to be cautious about extending the quantitative results reported here to general populations in malaria-endemic regions. Understanding how immune responses modify these statistical relationships given past exposure is key for being able to apply these results more broadly.

How long is the last mile? Evaluating successful malaria elimination trajectories.

BACKGROUND: Many national malaria programmes have set goals of eliminating malaria, but realistic timelines for achieving this goal remain unclear. In this investigation, historical data are collated on countries that successfully eliminated malaria to assess how long elimination has taken in the past, and thus to inform feasible timelines for achieving it in the future. METHODS: Annual malaria case series were sought for 56 successful elimination programmes through a non-systematic review. Up to 40 years of annual case counts were compiled leading up to the first year in which zero locally acquired or indigenous cases were reported. To separate the period over which effective elimination efforts occurred from prior background trends, annual case totals were log transformed, and their slopes evaluated for a breakpoint in linear trend using the segmented package in R. The number of years from the breakpoint to the first year with zero cases and the decline rate over that period were then calculated. Wilcox-Mann-Whitney tests were used to evaluate whether a set of territory characteristics were associated with the timelines and decline rates. RESULTS: Case series declining to the first year with zero cases were compiled for 45/56 of the candidate elimination programmes, and statistically significant breakpoints were identified for 42. The median timeline from the breakpoint to the first year with zero local cases was 12 years, over which cases declined at a median rate of 54% per year. Prior to the breakpoint, the median trend was slightly decreasing with median annual decline of < 3%. Timelines to elimination were fastest among territories that lacked land boundaries, had centroids in the Tropics, received low numbers of imported cases, and had elimination certified by the World Health Organization. CONCLUSION: The historical case series assembled here may help countries with aspirations of malaria elimination to set feasible milestones towards this goal. Setting goals for malaria elimination on short timescales may be most appropriate in isolated, low importation settings, such as islands, while other regions aiming to eliminate malaria must consider how to sustainably fund and maintain vital case management and vector control services until zero cases are reached.

Variation in Childhood Diarrheal Morbidity and Mortality in Africa, 2000-2015.

BACKGROUND: Diarrheal diseases are the third leading cause of disease and death in children younger than 5 years of age in Africa and were responsible for an estimated 30 million cases of severe diarrhea (95% credible interval, 27 million to 33 million) and 330,000 deaths (95% credible interval, 270,000 to 380,000) in 2015. The development of targeted approaches to address this burden has been hampered by a paucity of comprehensive, fine-scale estimates of diarrhea-related disease and death among and within countries. METHODS: We produced annual estimates of the prevalence and incidence of diarrhea and diarrhea-related mortality with high geographic detail (5 km2) across Africa from 2000 through 2015. Estimates were created with the use of Bayesian geostatistical techniques and were calibrated to the results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016. RESULTS: The results revealed geographic inequality with regard to diarrhea risk in Africa. Of the estimated 330,000 childhood deaths that were attributable to diarrhea in 2015, more than 50% occurred in 55 of the 782 first-level administrative subdivisions (e.g., states). In 2015, mortality rates among first-level administrative subdivisions in Nigeria differed by up to a factor of 6. The case fatality rates were highly varied at the national level across Africa, with the highest values observed in Benin, Lesotho, Mali, Nigeria, and Sierra Leone. CONCLUSIONS: Our findings showed concentrated areas of diarrheal disease and diarrhea-related death in countries that had a consistently high burden as well as in countries that had considerable national-level reductions in diarrhea burden. (Funded by the Bill and Melinda Gates Foundation.).

Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology.

Mosquitoes are important vectors for pathogens that infect humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we re-examine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for individual-based simulation models called MBITES (Mosquito Bout-based and Individual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While mosquito infection and pathogen development are one possible part of a mosquito's state, that is not our main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations' capacity to transmit pathogens.

Quantifying malaria acquired during travel and its role in malaria elimination on Bioko Island.

BACKGROUND: Malaria elimination is the goal for Bioko Island, Equatorial Guinea. Intensive interventions implemented since 2004 have reduced prevalence, but progress has stalled in recent years. A challenge for elimination has been malaria infections in residents acquired during travel to mainland Equatorial Guinea. The present article quantifies how off-island contributes to remaining malaria prevalence on Bioko Island, and investigates the potential role of a pre-erythrocytic vaccine in making further progress towards elimination. METHODS: Malaria transmission on Bioko Island was simulated using a model calibrated based on data from the Malaria Indicator Surveys (MIS) from 2015 to 2018, including detailed travel histories and malaria positivity by rapid-diagnostic tests (RDTs), as well as geospatial estimates of malaria prevalence. Mosquito population density was adjusted to fit local transmission, conditional on importation rates under current levels of control and within-island mobility. The simulations were then used to evaluate the impact of two pre-erythrocytic vaccine distribution strategies: mass treat and vaccinate, and prophylactic vaccination for off-island travellers. Lastly, a sensitivity analysis was performed through an ensemble of simulations fit to the Bayesian joint posterior probability distribution of the geospatial prevalence estimates. RESULTS: The simulations suggest that in Malabo, an urban city containing 80% of the population, there are some pockets of residual transmission, but a large proportion of infections are acquired off-island by travellers to the mainland. Outside of Malabo, prevalence was mainly attributable to local transmission. The uncertainty in the local transmission vs. importation is lowest within Malabo and highest outside. Using a pre-erythrocytic vaccine to protect travellers would have larger benefits than using the vaccine to protect residents of Bioko Island from local transmission. In simulations, mass treatment and vaccination had short-lived benefits, as malaria prevalence returned to current levels as the vaccine's efficacy waned. Prophylactic vaccination of travellers resulted in longer-lasting reductions in prevalence. These projections were robust to underlying uncertainty in prevalence estimates. CONCLUSIONS: The modelled outcomes suggest that the volume of malaria cases imported from the mainland is a partial driver of continued endemic malaria on Bioko Island, and that continued elimination efforts on must account for human travel activity.

Performance of passive case detection for malaria surveillance: results from nine countries in Mesoamerica and the Dominican Republic.

BACKGROUND: In malaria elimination settings, available metrics for malaria surveillance have been insufficient to measure the performance of passive case detection adequately. An indicator for malaria suspected cases with malaria test (MSCT) is proposed to measure the rate of testing on persons presenting to health facilities who satisfy the definition of a suspected malaria case. This metric does not rely on prior knowledge of fever prevalence, seasonality, or external denominators, and can be used to compare detection rates in suspected cases within and between countries, including across settings with different levels of transmission. METHODS: To compute the MSCT, an operational definition for suspected malaria cases was established, including clinical and epidemiological criteria. In general, suspected cases included: (1) persons with fever detected in areas with active malaria transmission; (2) persons with fever identified in areas with no active transmission and travel history to, or residence in areas with active transmission (either national or international); and (3) persons presenting with fever, chills and sweating from any area. Data was collected from 9 countries: Belize, Colombia (in areas with active transmission), Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras, Nicaragua, and Panama (September-March 2020). A sample of eligible medical records for 2018 was selected from a sample of health facilities in each country. An algorithm was constructed to assess if a malaria test was ordered or performed for cases that met the suspected case definition. RESULTS: A sample of 5873 suspected malaria cases was obtained from 239 health facilities. Except for Nicaragua and Colombia, malaria tests were requested in less than 10% of all cases. More cases were tested in areas with active transmission than areas without cases. Travel history was not systematically recorded in any country. CONCLUSIONS: A statistically comparable, replicable, and standardized metric was proposed to measure suspected malaria cases with a test (microscopy or rapid diagnostic test) that enables assessing the performance of passive case detection. Cross-country findings have important implications for malaria and infectious disease surveillance, which should be promptly addressed as countries progress towards malaria elimination. Local and easy-to-implement tools could be implemented to assess and improve passive case detection.

Associated patterns of insecticide resistance in field populations of malaria vectors across Africa.

The development of insecticide resistance in African malaria vectors threatens the continued efficacy of important vector control methods that rely on a limited set of insecticides. To understand the operational significance of resistance we require quantitative information about levels of resistance in field populations to the suite of vector control insecticides. Estimation of resistance is complicated by the sparsity of observations in field populations, variation in resistance over time and space at local and regional scales, and cross-resistance between different insecticide types. Using observations of the prevalence of resistance in mosquito species from the Anopheles gambiae complex sampled from 1,183 locations throughout Africa, we applied Bayesian geostatistical models to quantify patterns of covariation in resistance phenotypes across different insecticides. For resistance to the three pyrethroids tested, deltamethrin, permethrin, and λ-cyhalothrin, we found consistent forms of covariation across sub-Saharan Africa and covariation between resistance to these pyrethroids and resistance to DDT. We found no evidence of resistance interactions between carbamate and organophosphate insecticides or between these insecticides and those from other classes. For pyrethroids and DDT we found significant associations between predicted mean resistance and the observed frequency of kdr mutations in the Vgsc gene in field mosquito samples, with DDT showing the strongest association. These results improve our capacity to understand and predict resistance patterns throughout Africa and can guide the development of monitoring strategies.

Association Between the 5As and Stage of Change Among African American Smokers Eligible for Low-Dose Computed Tomography Screening.

We investigated the association between the 5As (Ask, Advise, Assess, Assist, and Arrange) clinical protocol and stage of change among African American smokers who are eligible for low-dose computed tomography screening. In 2019, 60 African American daily smokers aged 55 years or older were recruited in a large hospital in New Orleans, Louisiana. Smokers who received assistance for smoking cessation were more likely to be in the preparation stage than those who did not receive any assistance. Assistance from health professionals is an essential form of support and may substantially enhance smokers' motivation to quit smoking in this population that is at higher risk for mortality from lung cancer.

Mapping the global endemicity and clinical burden of Plasmodium vivax, 2000-17: a spatial and temporal modelling study.

BACKGROUND: Plasmodium vivax exacts a significant toll on health worldwide, yet few efforts to date have quantified the extent and temporal trends of its global distribution. Given the challenges associated with the proper diagnosis and treatment of P vivax, national malaria programmes-particularly those pursuing malaria elimination strategies-require up to date assessments of P vivax endemicity and disease impact. This study presents the first global maps of P vivax clinical burden from 2000 to 2017. METHODS: In this spatial and temporal modelling study, we adjusted routine malariometric surveillance data for known biases and used socioeconomic indicators to generate time series of the clinical burden of P vivax. These data informed Bayesian geospatial models, which produced fine-scale predictions of P vivax clinical incidence and infection prevalence over time. Within sub-Saharan Africa, where routine surveillance for P vivax is not standard practice, we combined predicted surfaces of Plasmodium falciparum with country-specific ratios of P vivax to P falciparum. These results were combined with surveillance-based outputs outside of Africa to generate global maps. FINDINGS: We present the first high-resolution maps of P vivax burden. These results are combined with those for P falciparum (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The burden of P vivax malaria decreased by 41·6%, from 24·5 million cases (95% uncertainty interval 22·5-27·0) in 2000 to 14·3 million cases (13·7-15·0) in 2017. The Americas had a reduction of 56·8% (47·6-67·0) in total cases since 2000, while South-East Asia recorded declines of 50·5% (50·3-50·6) and the Western Pacific regions recorded declines of 51·3% (48·0-55·4). Europe achieved zero P vivax cases during the study period. Nonetheless, rates of decline have stalled in the past five years for many countries, with particular increases noted in regions affected by political and economic instability. INTERPRETATION: Our study highlights important spatial and temporal patterns in the clinical burden and prevalence of P vivax. Amid substantial progress worldwide, plateauing gains and areas of increased burden signal the potential for challenges that are greater than expected on the road to malaria elimination. These results support global monitoring systems and can inform the optimisation of diagnosis and treatment where P vivax has most impact. FUNDING: Bill & Melinda Gates Foundation and the Wellcome Trust.

Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000-17: a spatial and temporal modelling study.

BACKGROUND: Since 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spatially heterogeneous patterns of disease risk and thus efficiently target areas of high burden. METHODS: We updated and refined the Plasmodium falciparum parasite rate and clinical incidence models for sub-Saharan Africa, which rely on cross-sectional survey data for parasite rate and intervention coverage. For malaria endemic countries outside of sub-Saharan Africa, we produced estimates of parasite rate and incidence by applying an ecological downscaling approach to malaria incidence data acquired via routine surveillance. Mortality estimates were derived by linking incidence to systematically derived vital registration and verbal autopsy data. Informed by high-resolution covariate surfaces, we estimated P falciparum parasite rate, clinical incidence, and mortality at national, subnational, and 5 × 5 km pixel scales with corresponding uncertainty metrics. FINDINGS: We present the first global, high-resolution map of P falciparum malaria mortality and the first global prevalence and incidence maps since 2010. These results are combined with those for Plasmodium vivax (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The P falciparum estimates span the period 2000-17, and illustrate the rapid decline in burden between 2005 and 2017, with incidence declining by 27·9% and mortality declining by 42·5%. Despite a growing population in endemic regions, P falciparum cases declined between 2005 and 2017, from 232·3 million (95% uncertainty interval 198·8-277·7) to 193·9 million (156·6-240·2) and deaths declined from 925 800 (596 900-1 341 100) to 618 700 (368 600-952 200). Despite the declines in burden, 90·1% of people within sub-Saharan Africa continue to reside in endemic areas, and this region accounted for 79·4% of cases and 87·6% of deaths in 2017. INTERPRETATION: High-resolution maps of P falciparum provide a contemporary resource for informing global policy and malaria control planning, programme implementation, and monitoring initiatives. Amid progress in reducing global malaria burden, areas where incidence trends have plateaued or increased in the past 5 years underscore the fragility of hard-won gains against malaria. Efforts towards elimination should be strengthened in such areas, and those where burden remained high throughout the study period. FUNDING: Bill & Melinda Gates Foundation.

An agent-based model of dengue virus transmission shows how uncertainty about breakthrough infections influences vaccination impact projections.

Prophylactic vaccination is a powerful tool for reducing the burden of infectious diseases, due to a combination of direct protection of vaccinees and indirect protection of others via herd immunity. Computational models play an important role in devising strategies for vaccination by making projections of its impacts on public health. Such projections are subject to uncertainty about numerous factors, however. For example, many vaccine efficacy trials focus on measuring protection against disease rather than protection against infection, leaving the extent of breakthrough infections (i.e., disease ameliorated but infection unimpeded) among vaccinees unknown. Our goal in this study was to quantify the extent to which uncertainty about breakthrough infections results in uncertainty about vaccination impact, with a focus on vaccines for dengue. To realistically account for the many forms of heterogeneity in dengue virus (DENV) transmission, which could have implications for the dynamics of indirect protection, we used a stochastic, agent-based model for DENV transmission informed by more than a decade of empirical studies in the city of Iquitos, Peru. Following 20 years of routine vaccination of nine-year-old children at 80% coverage, projections of the proportion of disease episodes averted varied by a factor of 1.76 (95% CI: 1.54-2.06) across the range of uncertainty about breakthrough infections. This was equivalent to the range of vaccination impact projected across a range of uncertainty about vaccine efficacy of 0.268 (95% CI: 0.210-0.329). Until uncertainty about breakthrough infections can be addressed empirically, our results demonstrate the importance of accounting for it in models of vaccination impact.

Identification and characterization of immature Anopheles and culicines (Diptera: Culicidae) at three sites of varying malaria transmission intensities in Uganda.

BACKGROUND: Over the last two decades, there has been remarkable progress in malaria control in sub-Saharan Africa, due mainly to the massive deployment of long-lasting insecticidal nets and indoor residual spraying. Despite these gains, it is clear that in many situations, additional interventions are needed to further reduce malaria transmission. The World Health Organization (WHO) has promoted the Integrated Vector Management (IVM) approach through its Global Vector Control Response 2017-2030. However, prior roll-out of larval source management (LSM) as part of IVM, knowledge on ecology of larval aquatic habitats is required. METHODS: Aquatic habitats colonized by immature Anopheles and culicines vectors were characterized at three sites of low, medium and high malaria transmission in Uganda from October 2011 to June 2015. Larval surveys were conducted along transects in each site and aquatic habitats described according to type and size. Immature Anopheles, culicines and pupae from the described habitats were sampled using standard dipping methods to determine larval and pupae densities. Larvae were identified as anopheline or culicine, and counted. Pupae were not identified further. Binary logistic regression analysis was used to identify factors associated with the presence of immature Anopheles and culicines in each site. RESULTS: A total of 1205 larval aquatic habitats were surveyed and yielded a total of 17,028 anopheline larvae, 26,958 culicine larvae and 1189 pupae. Peaks in larval abundance occurred in all sites in March-May and August-October coinciding with the rainy seasons. Anopheles larvae were found in 52.4% (n = 251) of aquatic habitats in Tororo, a site of high transmission, 41.9% (n = 536) of habitats in Kanungu, a site with moderate malaria transmission, and 15.8% (n = 418) in Jinja, a site with low malaria transmission. The odds of finding larvae was highest in rice fields compared to pools in both Tororo (odds ratio, OR = 4.21, 95% CI 1.22-14.56, p = 0.02) and Kanungu (OR = 2.14, 95% CI 1.12-4.07, p = 0.02), while in Jinja the odd were highest in containers (OR = 4.55, 95% CI = 1.09-19.14, p = 0.03). In Kanungu, larvae were less likely to be found in containers compared to pools (OR = 0.26, 95% CI 0.09-0.66, p = 0.008) and river fringe (OR = 0.19, 95% CI 0.07-0.52, p = 0.001). Medium sized habitats were associated with high odds of finding larvae compared to small habitats (OR = 3.59, 95% CI 1.18-14.19, p = 0.039). CONCLUSIONS: These findings show that immature Anopheles and culicines were common in areas of high and moderate transmission but were rare in areas of low transmission. Although immature Anopheles and culicines were found in all types of water bodies, they were most common in rice fields and less common in open drains and in river fringes. Methods are needed to reduce the aquatic stages of anopheline mosquitoes in human-made habitats, particularly rice fields.

Malaria outbreak in Riaba district, Bioko Island: lessons learned.

At the beginning of 2019, a sudden surge of malaria cases was observed in the district of Riaba, Bioko Island. Between January and April, confirmed malaria cases increased 3.8-fold compared to the same period in 2018. Concurrently, anopheline human biting rate (HBR) increased 2.1-fold. During the outbreak, 82.2% of the district population was tested for malaria with a rapid diagnostic test; 37.2% of those tested had a detectable infection and were treated according to national guidelines. Vector control interventions, including indoor residual spraying and larval source management were scaled-up. After the interventions, the number of confirmed cases decreased by 70% and the overall parasite prevalence in the communities by 43.8%. Observed prevalence in a follow up malaria indicator survey, however, was significantly higher than elsewhere on the island, and higher than in previous years. There was no significant reduction in HBR, which remained high for the rest of the year. The surge was attributed to various factors, chiefly increased rainfall and a large number of anthropogenic anopheline breeding sites created by construction works. This case study highlights the need for sustained vector control interventions and multi-sector participation, particularly in malaria control and elimination settings with persistently high local malaria receptivity.

Radiologic chest CT findings from COVID-19 in Orleans Parish, Louisiana.

Orleans Parish in Louisiana is in the midst of an exponentially increasing number of patient admissions with COVID-19 and respiratory symptoms. Patients have been described having CT findings most consistent with an early-stage (<7 days from symptoms onset) or an advanced stage (8-14 days from symptoms onset). We describe and illustrate those early and advanced stage CT findings from patients with documented COVID-19 who have been admitted to University Medical Center in New Orleans, Louisiana.