Assessing the relationship between operationally defined zero-dose communities and access to selected primary healthcare services for children and pregnant women in emergency settings.

In this study the authors examine the relationship between "zero-dose" communities and access to healthcare services. This was done by first ensuring the first dose of the Diphtheria Tetanus and Pertussis vaccine was a better measure of zero-dose communities than the measles-containing vaccine. Once ensured, it was used to examine the association with access to primary healthcare services for children and pregnant women in the Democratic Republic of Congo, Afghanistan, and Bangladesh. These services were divided into: a) unscheduled healthcare services such as birth assistance as well as seeking care and treatment for diarrheal diseases and cough/fever episodes and b) other scheduled health services such as antenatal care visits and vitamin A supplementation. Using recent Demographic Health Survey data (2014: Democratic Republic of Congo, 2015: Afghanistan, 2018: Bangladesh), data was analyzed via Chi Squared analysis or Fischer's Exact Test. If significant, a linear regression analysis was performed to examine if the association was linear. While the linear relationship observed between children who had received the first dose of the Diphtheria Tetanus and Pertussis vaccine (the reverse to zero-dose communities) and coverage of other vaccines was expected, the results of the regression analysis depicted an unexpected split in behavior. For scheduled and birth assistance health services, a linear relationship was generally observed. For unscheduled services associated with illness treatments, this was not the case. While it does not appear that the first dose of the Diphtheria Tetanus and Pertussis vaccine can be used to predict (at least in a linear manner) access to some primary (particularly illness treatment) healthcare services in emergency/ humanitarian settings, it can serve as an indirect measure of health services not associated with the treatment of childhood infections such as antenatal care, skilled birth assistance, and to a lesser degree even vitamin A supplementation.

Analyzing Health of Forcibly Displaced Communities through an Integrated Ecological Lens.

Health care among forcibly displaced persons is frequently driven by siloed approaches. Aspects of the built environment, social factors, and the bidirectional relationship between the changing ecosystem and residents are often ignored in health policy design and implementation. While recognizing factors that create a preference for siloed approaches and appreciating the work of humanitarian agencies, we argue for a new data-driven and holistic approach to understand the health of the forcibly displaced. It should be rooted in the realities of the emergence of new diseases, dynamic demographics, and degrading environments around the displaced communities. Such an approach envisions refugee and internally displaced camps as dynamic, complex ecosystems that alter, and are altered by, spatial and temporal factors. At the root of this approach is the necessity to work across disciplines, to think holistically, to go beyond treating single ailments, and to develop ethical approaches that provide dignity to those who are forcibly displaced.

A mathematical model to estimate the incidence of child wasting in Yemen.

INTRODUCTION: The ongoing civil war in Yemen has severely restricted imports of food and fuel, disrupted livelihoods and displaced millions, worsening already high pre-war levels of food insecurity. Paired with frequent outbreaks of disease and a collapsed health system, this has brought rates of wasting in children under five to the country's highest recorded levels, which continue to increase as the crisis worsens and aid becomes increasingly limited. In their planning of services to treat and prevent wasting in children, humanitarian agencies rely on a standard calculation to estimate the expected number of cases for the coming year, where incidence is estimated from prevalence and the average duration of an episode of wasting. The average duration of an episode of moderate and severe wasting is currently estimated at 7.5 months-a globally-used value derived from historical cohort studies. Given that incidence varies considerably by context-where food production and availability, treatment coverage and disease rates all vary-a single estimate cannot be applied to all contexts, and especially not a highly unstable crisis setting such as Yemen. While recent studies have aimed to derive context-specific incidence estimates in several countries, little has been done to estimate the incidence of both moderate and severe wasting in Yemen. METHODS: In order to provide context-specific estimates of the average duration of an episode, and resultingly, incidence correction factors for moderate and severe wasting, we have developed a Markov model. Model inputs were estimated using a combination of treatment admission and outcome records compiled by the Yemen Nutrition Cluster, 2018 and 2019 SMART surveys, and other estimates from the literature. The model derived estimates for the governorate of Lahj, Yemen; it was initialized using August 2018 SMART survey prevalence data and run until October 2019-the date of the subsequent SMART survey. Using a process of repeated model calibration, the incidence correction factors for severe wasting and moderate wasting were found, validating the resulting prevalence against the recorded value from the 2019 SMART survey. RESULTS: The average durations of an episode of moderate and severe wasting were estimated at 4.86 months, for an incidence correction factor k of 2.59, and 3.86 months, for an incidence correction factor k of 3.11, respectively. It was found that the annual caseload of moderate wasting was 36% higher and the annual caseload of severe wasting 58% higher than the originally-assumed values, estimated with k = 1.6. CONCLUSION: The model-derived incidence rates, consistent with findings from other contexts that a global incidence correction factor cannot be sufficient, allow for improved, context-specific estimates of the burden of wasting in Yemen. In crisis settings such as Yemen where funding and resources are extremely limited, the model's outputs holistically capture the burden of wasting in a way that may guide effective decision-making and may help ensure that limited resources are allocated most effectively.

Embedded multicellular spheroids as a biomimetic 3D cancer model for evaluating drug and drug-device combinations.

Multicellular aggregates of cells, termed spheroids, are of interest for studying tumor behavior and for evaluating the response of pharmacologically active agents. Spheroids more faithfully reproduce the tumor macrostructure found in vivo compared to classical 2D monolayers. We present a method for embedding spheroids within collagen gels followed by quantitative and qualitative whole spheroid and single cell analyses enabling characterization over the length scales from molecular to macroscopic. Spheroid producing and embedding capabilities are demonstrated for U2OS and MDA-MB-231 cell lines, of osteosarcoma and breast adenocarcinoma origin, respectively. Finally, using the MDA-MB-231 tumor model, the chemotherapeutic response between paclitaxel delivery as a bolus dose, as practiced in the clinic, is compared to delivery within an expansile nanoparticle. The expansile nanoparticle delivery route provides a superior outcome and the results mirror those observed in a murine xenograft model. These findings highlight the synergistic beneficial results that may arise from the use of a drug delivery system, and the need to evaluate both drug candidates and delivery systems in the research and preclinical screening phases of a new cancer therapy development program.

Bioengineering approaches to study multidrug resistance in tumor cells.

The ability of cancer cells to become resistant to chemotherapeutic agents is a major challenge for the treatment of malignant tumors. Several strategies have emerged to attempt to inhibit chemoresistance, but the fact remains that resistance is a problem for every effective anticancer drug. The first part of this review will focus on the mechanisms of chemoresistance. It is important to understand the environmental cues, transport limitations and the cellular signaling pathways associated with chemoresistance before we can hope to effectively combat it. The second part of this review focuses on the work that needs to be done moving forward. Specifically, this section focuses on the necessity of translational research and interdisciplinary directives. It is critical that the expertise of oncologists, biologists, and engineers be brought together to attempt to tackle the problem. This discussion is from an engineering perspective, as the dialogue between engineers and other cancer researchers is the most challenging due to non-overlapping background knowledge. Chemoresistance is a complex and devastating process, meaning that we urgently need sophisticated methods to study the process of how cells become resistant.