Host Nuclear Genome Copy Number Variations Identify High-Risk Anal Precancers in People Living with HIV.

BACKGROUND: People living with HIV (PLWH) have substantially increased incidence of anal precancer and cancer. There are very little data regarding genomic disturbances in anal precancers among PLWH. Here, we identified specific chromosomal variants in anal squamous intraepithelial lesions. METHODS: We collected 63 anal biopsy specimens (27 low-grade intraepithelial lesions [LSIL] and 36 high-grade intraepithelial lesions [HSIL]) from PLWH obtained as part of anal cancer screening in our NYC-based health system. Data on patient demographics, anal cytological and high-risk human papillomavirus (HR-HPV) diagnoses were collected. Specimens were tested for a panel of chromosomal alterations associated with HPV-induced oncogenesis using Fluorescence In-Situ Hybridization (FISH) and analyses compared the associations of these alterations with clinical characteristics. RESULTS: Gains of 3q26, 5p15, 20q13 and cen7 were detected in 42%, 31%, 31%, and 19% of HSIL compared to 7%, 0%, 4%, and 0% of LSIL, respectively. Where at least one abnormality was seen, 89% had a 3q26 gain. In lesions with 5p15 gains, 20q13 gains co-occurred in 91% of cases, while cen7 gain only co-occurred with the other three alterations. Sensitivity and specificity of any alteration to predict HSIL was 47% (95% CI: 30-65%) and 93% (95% CI: 76%-99%) respectively. CONCLUSIONS: Genomic alterations seen in HPV-associated cancers may help distinguish anal LSIL from HSIL. 3q26 amplification may be an early component of anal carcinogenesis, preceding 5p16, 20q13 and/or chr7. IMPACT: We share insights on potential genomic biomarkers for discriminating high-risk anal precancers.

Heterogeneity in elimination efforts could increase the risk of resurgence of lymphatic filariasis in Madagascar.

BACKGROUND: Progress in lymphatic filariasis (LF) elimination is spatially heterogeneous in many endemic countries, which may lead to resurgence in areas that have achieved elimination. Understanding the drivers and consequences of such heterogeneity could help inform strategies to reach global LF elimination goals by 2030. This study assesses whether differences in age-specific compliance with mass drug administration (MDA) could explain LF prevalence patterns in southeastern Madagascar and explores how spatial heterogeneity in prevalence and age-specific MDA compliance may affect the risk of LF resurgence after transmission interruption. METHODOLOGY: We used LYMFASIM model with parameters in line with the context of southeastern Madagascar and explored a wide range of scenarios with different MDA compliance for adults and children (40-100%) to estimate the proportion of elimination, non-elimination and resurgence events associated with each scenario. Finally, we evaluated the risk of resurgence associated with different levels of migration (2-6%) from surrounding districts combined with varying levels of LF microfilaria (mf) prevalence (0-24%) during that same study period. RESULTS: Differences in MDA compliance between adults and children better explained the observed heterogeneity in LF prevalence for these age groups than differences in exposure alone. The risk of resurgence associated with differences in MDA compliance scenarios ranged from 0 to 19% and was highest when compliance was high for children (e.g. 90%) and low for adults (e.g. 50%). The risk of resurgence associated with migration was generally higher, exceeding 60% risk for all the migration levels explored (2-6% per year) when mf prevalence in the source districts was between 9% and 20%. CONCLUSION: Gaps in the implementation of LF elimination programme can increase the risk of resurgence and undermine elimination efforts. In Madagascar, districts that have not attained elimination pose a significant risk for those that have achieved it. More research is needed to help guide LF elimination programme on the optimal strategies for surveillance and control that maximize the chances to sustain elimination and avoid resurgence.

Applying a zero-corrected, gravity model estimator reduces bias due to heterogeneity in healthcare utilization in community-scale, passive surveillance datasets of endemic diseases.

Data on population health are vital to evidence-based decision making but are rarely adequately localized or updated in continuous time. They also suffer from low ascertainment rates, particularly in rural areas where barriers to healthcare can cause infrequent touch points with the health system. Here, we demonstrate a novel statistical method to estimate the incidence of endemic diseases at the community level from passive surveillance data collected at primary health centers. The zero-corrected, gravity-model (ZERO-G) estimator explicitly models sampling intensity as a function of health facility characteristics and statistically accounts for extremely low rates of ascertainment. The result is a standardized, real-time estimate of disease incidence at a spatial resolution nearly ten times finer than typically reported by facility-based passive surveillance systems. We assessed the robustness of this method by applying it to a case study of field-collected malaria incidence rates from a rural health district in southeastern Madagascar. The ZERO-G estimator decreased geographic and financial bias in the dataset by over 90% and doubled the agreement rate between spatial patterns in malaria incidence and incidence estimates derived from prevalence surveys. The ZERO-G estimator is a promising method for adjusting passive surveillance data of common, endemic diseases, increasing the availability of continuously updated, high quality surveillance datasets at the community scale.

Morbidity and mortality burden of COVID-19 in rural Madagascar: results from a longitudinal cohort and nested seroprevalence study.

INTRODUCTION: Three years into the pandemic, there remains significant uncertainty about the true infection and mortality burden of COVID-19 in the World Health Organization Africa region. High quality, population-representative studies in Africa are rare and tend to be conducted in national capitals or large cities, leaving a substantial gap in our understanding of the impact of COVID-19 in rural, low-resource settings. Here, we estimated the spatio-temporal morbidity and mortality burden associated with COVID-19 in a rural health district of Madagascar until the first half of 2021. METHODS: We integrated a nested seroprevalence study within a pre-existing longitudinal cohort conducted in a representative sample of 1600 households in Ifanadiana District, Madagascar. Socio-demographic and health information was collected in combination with dried blood spots for about 6500 individuals of all ages, which were analysed to detect IgG and IgM antibodies against four specific proteins of SARS-CoV-2 in a bead-based multiplex immunoassay. We evaluated spatio-temporal patterns in COVID-19 infection history and its associations with several geographic, socio-economic and demographic factors via logistic regressions. RESULTS: Eighteen percent of people had been infected by April-June 2021, with seroprevalence increasing with individuals' age. COVID-19 primarily spread along the only paved road and in major towns during the first epidemic wave, subsequently spreading along secondary roads during the second wave to more remote areas. Wealthier individuals and those with occupations such as commerce and formal employment were at higher risk of being infected in the first wave. Adult mortality increased in 2020, particularly for older men for whom it nearly doubled up to nearly 40 deaths per 1000. Less than 10% of mortality in this period would be directly attributed to COVID-19 deaths if known infection fatality ratios are applied to observed seroprevalence in the district. CONCLUSION: Our study provides a very granular understanding on COVID-19 transmission and mortality in a rural population of sub-Saharan Africa and suggests that the disease burden in these areas may have been substantially underestimated.

Sociodemographic Variables Can Guide Prioritized Testing Strategies for Epidemic Control in Resource-Limited Contexts.

BACKGROUND: Targeted surveillance allows public health authorities to implement testing and isolation strategies when diagnostic resources are limited, and can be implemented via the consideration of social network topologies. However, it remains unclear how to implement such surveillance and control when network data are unavailable. METHODS: We evaluated the ability of sociodemographic proxies of degree centrality to guide prioritized testing of infected individuals compared to known degree centrality. Proxies were estimated via readily available sociodemographic variables (age, gender, marital status, educational attainment, household size). We simulated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics via a susceptible-exposed-infected-recovered individual-based model on 2 contact networks from rural Madagascar to test applicability of these findings to low-resource contexts. RESULTS: Targeted testing using sociodemographic proxies performed similarly to targeted testing using known degree centralities. At low testing capacity, using proxies reduced infection burden by 22%-33% while using 20% fewer tests, compared to random testing. By comparison, using known degree centrality reduced the infection burden by 31%-44% while using 26%-29% fewer tests. CONCLUSIONS: We demonstrate that incorporating social network information into epidemic control strategies is an effective countermeasure to low testing capacity and can be implemented via sociodemographic proxies when social network data are unavailable.

Climatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors: Evidence from rural Madagascar.

While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria dynamics in rural Madagascar, estimated from facility-based passive surveillance data. Specifically, this study integrates climate, land-use, and representative household survey data to explain and predict malaria dynamics at a high spatial resolution (i.e., by Fokontany, a cluster of villages) relevant to health care practitioners. Combining generalized linear mixed models (GLMM) and path analyses, we found that socio-economic, land use and climatic variables are all important predictors of monthly malaria incidence at fine spatial scales, via both direct and indirect effects. In addition, out-of-sample predictions from our model were able to identify 58% of the Fokontany in the top quintile for malaria incidence and account for 77% of the variation in the Fokontany incidence rank. These results suggest that it is possible to build a predictive framework using environmental and social predictors that can be complementary to standard surveillance systems and help inform control strategies by field actors at local scales.

The Burden of Cardiac Implantable Electronic Device Checks in the Peri-MRI Setting: The CHECK-MRI Study.

BACKGROUND: Most modern cardiac implantable electronic device (CIED) systems are now compatible with magnetic resonance imaging (MRI) scans. The requirement for both pre- and post-MRI CIED checks imposes significant workload to the cardiac electrophysiology service. Here, we sought to determine the burden of CIED checks associated with MRI scans. METHODS: We identified all CIED checks performed peri-MRI scans at our institution over a 3-year period between 1 July 2017 to 30 June 2020, comprising three separate financial years (FY). Device check reports, MRI scan reports and clinical summaries were collated. The workload burden was determined by assessing the occasions and duration of service. Analysis was performed to determine cost burden/projections for this service and identify factors contributing to the workload. RESULTS: A total of 739 CIED checks were performed in the peri-MRI scan setting (370 pre- and 369 post-MRI scan), including 5% (n=39) that were performed outside of routine hours (weekday <8 am or >5 pm, and weekends). MRIs were performed for 295 patients (75±13 years old, 64% male) with a CIED (88% permanent pacemaker, and 12% high voltage device), including 49 who had more than one MRI scan. The proportion of total MRI scans for patients with a CIED in-situ increased each FY (from 0.5% of all MRIs in FY1, to 0.9% in FY2, to 1.0% in FY3). The weekly workload increased (R2=0.2, p<0.001), but with week-to-week variability due to ad hoc scheduling (209 days with only one MRI vs 78 days with ≥2 MRIs for CIED patients). The projected annual cost of this service will increase to AUD$161,695 in 10 years for an estimated annual 546 MRI scans for CIED patients. CONCLUSIONS: There is an increasing workload burden and expense associated with CIED checks in the peri-MRI setting. Appropriate budgeting, staff allocation and standardisation of automated CIED pre-programming features among manufacturers are urgently needed.

Correction: Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models.

[This corrects the article DOI: 10.1371/journal.pntd.0005568.].

A Data-driven Horizon Scan of Bacterial Pathogens at the Wildlife-livestock Interface.

Many livestock diseases rely on wildlife for the transmission or maintenance of the pathogen, and the wildlife-livestock interface represents a potential site of disease emergence for novel pathogens in livestock. Predicting which pathogen species are most likely to emerge in the future is an important challenge for infectious disease surveillance and intelligence. We used a machine learning approach to conduct a data-driven horizon scan of bacterial associations at the wildlife-livestock interface for cows, sheep, and pigs. Our model identified and ranked from 76 to 189 potential novel bacterial species that might associate with each livestock species. Wildlife reservoirs of known and novel bacteria were shared among all three species, suggesting that targeting surveillance and/or control efforts towards these reservoirs could contribute disproportionately to reducing spillover risk to livestock. By predicting pathogen-host associations at the wildlife-livestock interface, we demonstrate one way to plan for and prevent disease emergence in livestock.

Prioritizing COVID-19 vaccination efforts and dose allocation within Madagascar.

BACKGROUND: While mass COVID-19 vaccination programs are underway in high-income countries, limited availability of doses has resulted in few vaccines administered in low and middle income countries (LMICs). The COVID-19 Vaccines Global Access (COVAX) is a WHO-led initiative to promote vaccine access equity to LMICs and is providing many of the doses available in these settings. However, initial doses are limited and countries, such as Madagascar, need to develop prioritization schemes to maximize the benefits of vaccination with very limited supplies. There is some consensus that dose deployment should initially target health care workers, and those who are more vulnerable including older individuals. However, questions of geographic deployment remain, in particular associated with limits around vaccine access and delivery capacity in underserved communities, for example in rural areas that may also include substantial proportions of the population. METHODS: To address these questions, we developed a mathematical model of SARS-CoV-2 transmission dynamics and simulated various vaccination allocation strategies for Madagascar. Simulated strategies were based on a number of possible geographical prioritization schemes, testing sensitivity to initial susceptibility in the population, and evaluating the potential of tests for previous infection. RESULTS: Using cumulative deaths due to COVID-19 as the main outcome of interest, our results indicate that distributing the number of vaccine doses according to the number of elderly living in the region or according to the population size results in a greater reduction of mortality compared to distributing doses based on the reported number of cases and deaths. The benefits of vaccination strategies are diminished if the burden (and thus accumulated immunity) has been greatest in the most populous regions, but the overall strategy ranking remains comparable. If rapid tests for prior immunity may be swiftly and effectively delivered, there is potential for considerable gain in mortality averted, but considering delivery limitations modulates this. CONCLUSION: At a subnational scale, our results support the strategy adopted by the COVAX initiative at a global scale.

Effects of Multisession Prefrontal Transcranial Direct Current Stimulation on Long-term Memory and Working Memory in Older Adults.

Transcranial direct current stimulation (tDCS) is a noninvasive form of electrical brain stimulation popularly used to augment the effects of working memory (WM) training. Although success has been mixed, some studies report enhancements in WM performance persisting days, weeks, or even months that are actually more reminiscent of consolidation effects typically observed in the long-term memory (LTM) domain, rather than WM improvements per se. Although tDCS has been often reported to enhance both WM and LTM, these effects have never been directly compared within the same study. However, given their considerable neural and behavioral overlap, this is a timely comparison to make. This study reports results from a multisession intervention in older adults comparing active and sham tDCS over the left dorsolateral pFC during training on both an n-back WM task and a word learning LTM task. We found strong and robust effects on LTM, but mixed effects on WM that only emerged for those with lower baseline ability. Importantly, mediation analyses showed an indirect effect of tDCS on WM that was mediated by improvements in consolidation. We conclude that tDCS over the left dorsolateral pFC can be used as an effective intervention to foster long-term learning and memory consolidation in aging, which can manifest in performance improvements across multiple memory domains.

Both consumptive and non-consumptive effects of predators impact mosquito populations and have implications for disease transmission.

Predator-prey interactions influence prey traits through both consumptive and non-consumptive effects, and variation in these traits can shape vector-borne disease dynamics. Meta-analysis methods were employed to generate predation effect sizes by different categories of predators and mosquito prey. This analysis showed that multiple families of aquatic predators are effective in consumptively reducing mosquito survival, and that the survival of Aedes, Anopheles, and Culex mosquitoes is negatively impacted by consumptive effects of predators. Mosquito larval size was found to play a more important role in explaining the heterogeneity of consumptive effects from predators than mosquito genus. Mosquito survival and body size were reduced by non-consumptive effects of predators, but development time was not significantly impacted. In addition, Culex vectors demonstrated predator avoidance behavior during oviposition. The results of this meta-analysis suggest that predators limit disease transmission by reducing both vector survival and vector size, and that associations between drought and human West Nile virus cases could be driven by the vector behavior of predator avoidance during oviposition. These findings are likely to be useful to infectious disease modelers who rely on vector traits as predictors of transmission.

Mosquitoes are often referred to as the deadliest animals on earth because some species spread malaria, West Nile virus or other dangerous diseases when they bite humans and other animals. Adult mosquitoes fly to streams, ponds and other freshwater environments to lay their eggs. When the eggs hatch, the young mosquitoes live in the water until they are ready to grow wings and transform into adults. In the water, the young mosquitoes are particularly vulnerable to being eaten by dragonfly larvae, fish and other predators. When adult females are choosing where to lay their eggs, they can use their sense of smell to detect these predators and attempt to avoid them. Along with eating the mosquitoes, the predators may also reduce mosquito populations in other ways. For example, predators can disrupt feeding among young mosquitoes, which may affect the time that it takes for them to grow into adults or the size of their bodies once they reach the adult stage. Although the impacts of different predators have been tested separately in multiple settings, the overall effects of predators on the ability of mosquitoes to spread diseases to humans remain unclear. To address this question, Russell, Herzog et al. used an approach called meta-analysis on data from previous studies. The analysis found that along with increasing the death rates of mosquitoes, the presence of predators also leads to a reduction in the body size of those mosquitoes that survive, causing them to have shorter lifespans and fewer offspring. Russell, Herzog et al. found that one type of mosquito known as Culex ­ which carries West Nile virus ­ avoided laying its eggs near predators. During droughts, increased predation in streams, ponds and other aquatic environments may lead adult female Culex mosquitoes to lay their eggs closer to residential areas with fewer predators. Russell, Herzog et al. propose that this may be one reason why outbreaks of West Nile virus in humans are more likely to occur during droughts. In the future, these findings may help researchers to predict outbreaks of West Nile virus, malaria and other diseases carried by mosquitoes more accurately. Furthermore, the work of Russell, Herzog et al. provides examples of mosquito predators that could be used as biocontrol agents to decrease numbers of mosquitoes in certain regions.

Effectiveness of eccentric-biased exercise interventions in reducing the incidence of falls and improving functional performance in older adults: a systematic review.

BACKGROUND: Exercise has been known to preserve and enhance functional performance in older adults. Eccentric exercise involves muscle contractions characterised by unique features such as lengthening of the muscle-tendon complex by a greater opposing force. AIMS: To systematically review randomised-controlled trials (RCTs) investigating the effectiveness of eccentric exercises in reducing the incidence of falls and improving the functional performance in older adults. KEY METHODS: We conducted a systematic review of RCTs following the PRISMA-P guidelines. Searches were completed in the Cochrane Central Register of Controlled Trials, Embase, CINAHL, Medline, and Global Health CABI. We included RCTs reporting at least one of the following outcomes-falls, Berg balance scale, timed-up and go test, chair stand test, stair climb test, maximal walking speed, and minute walking distance. Two reviewers screened papers for eligibility and assessed the quality of included papers using the Cochrane Collaborative risk-of-bias tool for randomised trials. Data were extracted by a single reviewer and cross-checked by the second reviewer. A narrative synthesis was undertaken, given the high level of heterogeneity across studies. RESULTS: Ten studies were assessed as eligible for inclusion in the review. Overall, eccentric exercises were as effective as conventional resistance exercises in improving the selected outcomes by most studies. Additionally, when pre-exercise and post-eccentric exercise functional performance measures were compared, there was a statistically significant improvement in nearly all measures. The quality of trials was mixed (one high, four moderate, two low-moderate, and three low risk of bias). CONCLUSIONS: Our systematic review suggests that eccentric exercises can be as effective as conventional exercises in older adults. Evidence suggests that such exercise interventions can lead to an improvement in geriatric function.

Decision-making experiences of young adults with long-term conditions.

BACKGROUND: Young adults with long-term conditions can struggle to accept their diagnosis and can become overwhelmed with managing their condition. Suboptimal transfer from paediatric to adult services with a resultant disengagement with the service can result in less involvement in care and decision-making. Shared decision-making can improve involvement in health decisions and increase satisfaction with treatment/therapy and care. OBJECTIVES: An integrative literature review was conducted to explore and understand young adults' experiences of decision-making in health care. DESIGN: An integrative literature review. DATA SOURCES: CINAHL, EMCARE, PsycINFO, HMIC, EMBASE, Web of Science, PubMed, MEDLINE, EBSCOHOST and COCHRANE databases were searched for relevant literature published between January 1999 and January 2020. FINDINGS: Thirteen primary research papers met the inclusion criteria. Four main themes were identified: (1) Information delivery and communication; (2) participation in decision-making; (3) social factors influencing decision-making and (4) emotional impact of decision-making. CONCLUSIONS: Young adults with long-term conditions have specific decision-making needs which can impact their emotional health. Research with a specific focus on young adults' experiences of decision-making in health care is needed.

Geographic barriers to care persist at the community healthcare level: Evidence from rural Madagascar.

Geographic distance is a critical barrier to healthcare access, particularly for rural communities with poor transportation infrastructure who rely on non-motorized transportation. There is broad consensus on the importance of community health workers (CHWs) to reduce the effects of geographic isolation on healthcare access. Due to a lack of fine-scale spatial data and individual patient records, little is known about the precise effects of CHWs on removing geographic barriers at this level of the healthcare system. Relying on a high-quality, crowd-sourced dataset that includes all paths and buildings in the area, we explored the impact of geographic distance from CHWs on the use of CHW services for children under 5 years in the rural district of Ifanadiana, southeastern Madagascar from 2018-2021. We then used this analysis to determine key features of an optimal geographic design of the CHW system, specifically optimizing a single CHW location or installing additional CHW sites. We found that consultation rates by CHWs decreased with increasing distance patients travel to the CHW by approximately 28.1% per km. The optimization exercise revealed that the majority of CHW sites (50/80) were already in an optimal location or shared an optimal location with a primary health clinic. Relocating the remaining CHW sites based on a geographic optimum was predicted to increase consultation rates by only 7.4%. On the other hand, adding a second CHW site was predicted to increase consultation rates by 31.5%, with a larger effect in more geographically dispersed catchments. Geographic distance remains a barrier at the level of the CHW, but optimizing CHW site location based on geography alone will not result in large gains in consultation rates. Rather, alternative strategies, such as the creation of additional CHW sites or the implementation of proactive care, should be considered.

Integrating Health Systems and Science to Respond to COVID-19 in a Model District of Rural Madagascar.

There are many outstanding questions about how to control the global COVID-19 pandemic. The information void has been especially stark in the World Health Organization Africa Region, which has low per capita reported cases, low testing rates, low access to therapeutic drugs, and has the longest wait for vaccines. As with all disease, the central challenge in responding to COVID-19 is that it requires integrating complex health systems that incorporate prevention, testing, front line health care, and reliable data to inform policies and their implementation within a relevant timeframe. It requires that the population can rely on the health system, and decision-makers can rely on the data. To understand the process and challenges of such an integrated response in an under-resourced rural African setting, we present the COVID-19 strategy in Ifanadiana District, where a partnership between Malagasy Ministry of Public Health (MoPH) and non-governmental organizations integrates prevention, diagnosis, surveillance, and treatment, in the context of a model health system. These efforts touch every level of the health system in the district-community, primary care centers, hospital-including the establishment of the only RT-PCR lab for SARS-CoV-2 testing outside of the capital. Starting in March of 2021, a second wave of COVID-19 occurred in Madagascar, but there remain fewer cases in Ifanadiana than for many other diseases (e.g., malaria). At the Ifanadiana District Hospital, there have been two deaths that are officially attributed to COVID-19. Here, we describe the main components and challenges of this integrated response, the broad epidemiological contours of the epidemic, and how complex data sources can be developed to address many questions of COVID-19 science. Because of data limitations, it still remains unclear how this epidemic will affect rural areas of Madagascar and other developing countries where health system utilization is relatively low and there is limited capacity to diagnose and treat COVID-19 patients. Widespread population based seroprevalence studies are being implemented in Ifanadiana to inform the COVID-19 response strategy as health systems must simultaneously manage perennial and endemic disease threats.

Care disruptions among patients with lung cancer: A COVID-19 and cancer outcomes study.

INTRODUCTION: Patients with lung cancer (LC) are susceptible to severe outcomes from COVID-19. This study evaluated disruption to care of patients with LC during the COVID-19 pandemic. METHODS: The COVID-19 and Cancer Outcomes Study (CCOS) is a prospective cohort study comprised of patients with a current or past history of hematological or solid malignancies with outpatient visits between March 2 and March 6, 2020, at two academic cancer centers in the Northeastern United States (US). Data was collected for the three months prior to the index week (baseline period) and the following three months (pandemic period). RESULTS: 313 of 2365 patients had LC, 1578 had other solid tumors, and 474 had hematological malignancies. Patients with LC were not at increased risk of COVID-19 diagnosis compared to patients with other solid or hematological malignancies. When comparing data from the pandemic period to the baseline period, patients with LC were more likely to have a decrease in in-person visits compared to patients with other solid tumors (aOR 1.94; 95% CI, 1.46-2.58), but without an increase in telehealth visits (aOR 1.13; 95% CI 0.85-1.50). Patients with LC were more likely to experience pandemic-related treatment delays than patients with other solid tumors (aOR 1.80; 95% CI 1.13-2.80) and were more likely to experience imaging/diagnostic procedure delays than patients with other solid tumors (aOR 2.59; 95% CI, 1.46-4.47) and hematological malignancies (aOR 2.01; 95% CI, 1.02-3.93). Among patients on systemic therapy, patients with LC were also at increased risk for decreased in-person visits and increased treatment delays compared to those with other solid tumors. DISCUSSION: Patients with LC experienced increased cancer care disruption compared to patients with other malignancies during the early phase of the COVID-19 pandemic. Focused efforts to ensure continuity of care for this patient population are warranted.

Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrhoeal disease in Ifanadiana, rural Madagascar.

Precision health mapping is a technique that uses spatial relationships between socio-ecological variables and disease to map the spatial distribution of disease, particularly for diseases with strong environmental signatures, such as diarrhoeal disease (DD). While some studies use GPS-tagged location data, other precision health mapping efforts rely heavily on data collected at coarse-spatial scales and may not produce operationally relevant predictions at fine enough spatio-temporal scales to inform local health programmes. We use two fine-scale health datasets collected in a rural district of Madagascar to identify socio-ecological covariates associated with childhood DD. We constructed generalized linear mixed models including socio-demographic, climatic and landcover variables and estimated variable importance via multi-model inference. We find that socio-demographic variables, and not environmental variables, are strong predictors of the spatial distribution of disease risk at both individual and commune-level (cluster of villages) spatial scales. Climatic variables predicted strong seasonality in DD, with the highest incidence in colder, drier months, but did not explain spatial patterns. Interestingly, the occurrence of a national holiday was highly predictive of increased DD incidence, highlighting the need for including cultural factors in modelling efforts. Our findings suggest that precision health mapping efforts that do not include socio-demographic covariates may have reduced explanatory power at the local scale. More research is needed to better define the set of conditions under which the application of precision health mapping can be operationally useful to local public health professionals.

Assessing temperature-dependent competition between two invasive mosquito species.

Invasive mosquitoes are expanding their ranges into new geographic areas and interacting with resident mosquito species. Understanding how novel interactions can affect mosquito population dynamics is necessary to predict transmission risk at invasion fronts. Mosquito life-history traits are extremely sensitive to temperature, and this can lead to temperature-dependent competition between competing invasive mosquito species. We explored temperature-dependent competition between Aedes aegypti and Anopheles stephensi, two invasive mosquito species whose distributions overlap in India, the Middle East, and North Africa, where An. stephensi is currently expanding into the endemic range of Ae. aegypti. We followed mosquito cohorts raised at different intraspecific and interspecific densities across five temperatures (16-32°C) to measure traits relevant for population growth and to estimate species' per capita growth rates. We then used these growth rates to derive each species' competitive ability at each temperature. We find strong evidence for asymmetric competition at all temperatures, with Ae. aegypti emerging as the dominant competitor. This was primarily because of differences in larval survival and development times across all temperatures that resulted in a higher estimated intrinsic growth rate and competitive tolerance estimate for Ae. aegypti compared to An. stephensi. The spread of An. stephensi into the African continent could lead to urban transmission of malaria, an otherwise rural disease, increasing the human population at risk and complicating malaria elimination efforts. Competition has resulted in habitat segregation of other invasive mosquito species, and our results suggest that it may play a role in determining the distribution of An. stephensi across its invasive range.