Introduction: Low rates of follow up with mental health treatments, and medication non-adherence are common among patients with Major Depressive Disorder (MDD), more so in low-middle income countries (LMIC). While mobile mental health has the potential to address this problem in resource-poor settings, the feasibility and acceptability of its use in rural women is unknown. We aimed to explore barriers to access and adherence to mental health treatment, and the feasibility of using mobile health to address these barriers among women with MDD in rural south India. Methods: Six focus groups were conducted among women with MDD (n=69) seeking care at a rural community health center in South India. Discussion centered on barriers to mental health treatment access and adherence and attitudes toward use of technology in addressing these barriers. We transcribed the discussions and analyzed them using qualitative analysis software. Results: Reasons for non-adherence were: transcultural explanatory model of illness; structural, financial and social barriers to access, and medication side-effects. Women were unenthusiastic about mobile health solutions due to illiteracy, lack of family support, unfamiliarity with use of mobile devices, lack of access to mobile phones and preference for in-person clinical consultation. Conclusions: This qualitative study examines the acceptability of mobile-mental health as a strategy to address barriers to depression treatment access and adherence among women in a rural setting. There are several barriers to adoption of mobile mental health technology in LMIC. It is important to address these barriers before implementing mobile health based solutions.

Background:The SARS-Cov-2 infection has rapidly saturated health systems and traditional surveillance networks are finding hard to keep pace with its spread. We designed a participatory disease surveillance (PDS) system, to capture symptoms of Influenza-like illness (ILI) to estimate SARS-CoV-2 infection in the community.Objective: While data generated by these platforms can help public health organisations find community hotspots and effectively direct control measures, it has never been compared to traditional systems.Methods: A completely anonymised web based PDS system, www.trackcovid-19.org was developed. We evaluated the symptomatic responses received form the PDS system to the traditional risk based surveillance carried out by the Bruhat Bengaluru Mahanagara Palike over a period of 45 days in the South Indian city of Bengaluru Results: The PDS system recorded 11062 entries from 106 Postal codes. A healthy response was obtained from 10863 users while 199 (1.8%) reported symptomatic. Subgroup analysis of a 14 day symptomatic window recorded 33 (0.29%) responses. Risk based surveillance was carried out covering a population of 605,284 with 209 (0.03%) individuals identified symptomatic.Conclusions: Web PDS platforms provide better visualisation of community infection when compared to traditional risk based surveillance systems. They are extremely useful by providing real time information in the extended battle against this pandemic. When integrated into national disease surveillance systems, they can provide long term community surveillance adding an important cost-effective layer to already available data sources.

BACKGROUND The SARS-Cov-2 infection has rapidly saturated health systems and traditional surveillance networks are finding hard to keep pace with its spread. We designed a participatory disease surveillance (PDS) system, to capture symptoms of Influenza-like illness (ILI) to estimate SARS-CoV-2 infection in the community. OBJECTIVE While data generated by these platforms can help public health organisations find community hotspots and effectively direct control measures, it has never been compared to traditional systems. METHODS A completely anonymised web based PDS system, www.trackcovid-19.org was developed. We evaluated the symptomatic responses received form the PDS system to the traditional risk based surveillance carried out by the Bruhat Bengaluru Mahanagara Palike over a period of 45 days in the South Indian city of Bengaluru RESULTS The PDS system recorded 11062 entries from 106 Postal codes. A healthy response was obtained from 10863 users while 199 (1.8%) reported symptomatic. Subgroup analysis of a 14 day symptomatic window recorded 33 (0.29%) responses. Risk based surveillance was carried out covering a population of 605,284 with 209 (0.03%) individuals identified symptomatic. CONCLUSIONS Web PDS platforms provide better visualisation of community infection when compared to traditional risk based surveillance systems. They are extremely useful by providing real time information in the extended battle against this pandemic. When integrated into national disease surveillance systems, they can provide long term community surveillance adding an important cost-effective layer to already available data sources.

patients, including CD86 (2.8-fold increase in classic monocytes, p¼0.06) and CCR2 (2.9-fold in intermediate monocytes, p¼0.17; 11-fold in non-classic monocytes, p¼0.03). Conclusions:In cancer patients presenting with severe SARS-CoV-2 positive pneumonia, the infection may cause a hypercoagulable state, as suggested by higher levels of D-dimer, and unleash a pro-inflammatory response. Marked CD4 + T lymphocytopenia and NK expansion may reflect lymphocyte exhaustion and dysregulated cytotoxicity. Monocyte activation and recruitment also seem to be strongly upregulated.Legal entity responsible for the study: Hospital Clínico San Carlos.

Background: The COVID-19 pandemic has meant a change in health care worldwide, and cancer patients are a particularly vulnerable population with their own clinical and therapeutic characteristics. Due to the lack of new evidence on what the best approach should be in the context of the current pandemic, it is essential to go further in the knowledge of the characteristics of this infection in cancer patients and its outcomes.Methods: From March 1 to April 30, 2020, we collected and analysed data of 1202 cancer patients who were under active treatment or follow-up at the Medical Oncology Department of La Princesa Hospital and had a COVID-19 PCR test due to clinical symptoms (216 patients tested).Results: We detected a total of 50 patients with positive PCR (a 4,1% of the total number of patients in the period analysed). The mean age at diagnosis of the infection was 69, 52% were women and 16% smokers. The most frequent diagnoses were breast cancer (28%), colon cancer (26%), and lung cancer (14%) (Figure 1). 60% were localized stages, 36% were undergoing chemotherapy and 8% with immunotherapy. Fourteen of the 50 infected patients died (28%), Thirty-seven patients (74%) required hospitalization, with a mean age of 73. Twenty patients received high-dose corticosteroids and four Tocilizumab. One patient was admitted to the ICU. Hospital mortality was 35.1%, being 57% male and with a mean age of 80. Three patients presented grade 3 neutropenia at diagnosis, none of whom died. Two hospitalized patients were diagnosed of acute pulmonary thromboembolism regarding to coronavirus infection. Conclusions:The aggressiveness of COVID-19 infection in cancer patients is high. In our center we had an incidence of 4.1%, an admission rate of 74%, an overall mortality rate of 28%, and a hospital mortality rate of 35%. These figures are higher than those described in non-oncological population. Neutropenia did not seem to be a poor prognostic factor among infected patients in our series.Legal entity responsible for the study: The authors.