Provision of community mental health care before and during the COVID-19 pandemic: A time series analysis in Peru.

BACKGROUND: A consequence of the COVID-19 pandemic was that the provision of mental health services was reduced in several countries around the world, while the demand for mental health services increased. AIMS: Our study aims to determine any variation in the number of users served, health appointments, and care activities conducted at 58 Peruvian community mental health centers (CMHCs) between March 2019 and October 2021. METHODS: Our study used an observational design and analyzed information from the care provided in CMHCs. We evaluate the number of users served, health appointments, and care activities performed per month. The main statistical analysis used segmented regression with Newey-West standard errors, taking into account each month of the evaluation. RESULTS: We had 988,456 unique users during the period evaluated. Regarding diagnoses, 7.4% (n = 72,818) had a severe mental problem, 39.4% (n = 389,330) a common mental problem, and 53.2% (n = 526,308) others health problems. The study found a reduction in the number of users served and health care appointments at the 58 CMHCs in March 2020, the month in which the closure measures were declared to reduce COVID-19 infections in Peru. This reduction was followed by an upward trend in the three variables during the pandemic in the 58 CMHCs studied. In, November 2020, 9 months after the pandemic started, the deficit in the average number of users served per month was recovered. CONCLUSIONS: Our study suggests that CMHCs in the Peruvian system were able to regain care capacity approximately 1 year after the pandemic. In addition, we discuss the efforts made to respond to mental health needs in the context of a global health crisis.

Profiles of depressive symptoms in Peru: An 8-year analysis in population-based surveys.

Background Profiles of depressive symptoms have been described due to heterogeneity in symptomatology and presentation. In our study, we estimate depressive symptom profiles and relate these symptom profiles to risk factors in the Peruvian population. Methods We carried out an observational study based on the Peruvian Demographic and Health Survey (2014-2022). Men and women aged 15 years and older living in urban and rural areas in all regions of Peru were included. The Patient Health Questionnaire-9 was used to define depressive symptom profiles. We estimated latent class models to define the profiles and performed a Poisson regression analysis to determine the associated factors. Results A total of 259,655 participants were included. The three-class model was found to be the most appropriate, and the classes were defined according to the severity of depressive symptoms (moderate-severe symptoms, mild symptoms, and without depressive symptoms). Also, it was found that the three classes identified have not changed during the years of evaluations, presenting very similar prevalence over the years. In addition, women are more likely than men to belong to a class with more severe depressive symptoms; and the older the age, the higher the probability of belonging to a class with greater severity of depressive symptoms. Conclusions Our study found that at the population level in Peru, depressive symptoms are grouped into three classes according to the intensity of the symptomatology present (no symptoms, mild symptoms and moderate-severe symptoms).