COVID-19 among Amazonian indigenous in Peru: mortality, incidence, and clinical characteristics

Mortality from COVID-19 in Amazonian and Andean original indigenous populations of Peru

OBJECTIVE

To compare the mortality rates from COVID-19 among indigenous populations of the Amazon and Andean regions of Peru during the years 2020, 2021 and 2022.

METHODS

Secondary analysis of 33,567 data from the COVID-19 Notification System of the National Epidemiology Center, Prevention and Control of Diseases (CDC-Peru), from the years 2020-2022. The variables were age, sex, belonging to the Andean or Amazonian ethnic group, number and type of symptoms and risk conditions, abnormal findings in chest X-rays, year of data collection for hospitalization and death from COVID-19. Poisson family generalized linear regression models with logarithmic linkage and robust variance were used to establish differences in mortality between ethnic groups. Crude and adjusted risk ratio (RR) with 95 % confidence intervals (CI) were calculated.

RESULTS

33,567 participants with an average age of 33.6 years were included, 44.4 % were men and 70.2 % belonged to the Amazonian ethnic group. Most of those affected by COVID-19 presented 2 symptoms (38.8 %), 4.8 % presented some risk condition, 1451 (4.3 %) were hospitalized, and 433 (1.3 %) died. The adjusted analysis showed that the Andean group, compared to the Amazonian, tended to have a higher probability of death, and this association was statistically significant, RR =7.6, 95 % CI (5.5-10.5).

CONCLUSIONS

Patients from Andean indigenous communities had an almost 8 times higher risk of death from COVID-19.

Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru

The COVID-19 pandemic has caused widespread infections, deaths, and substantial economic losses. Vaccine development efforts have led to authorized candidates reducing hospitalizations and mortality, although variant emergence remains a concern. Peru faced a significant impact due to healthcare deficiencies. This study employed logistic regression to mathematically model COVID-19's dynamics in Peru over three years and assessed the correlations between cases, deaths, and people vaccinated. We estimated the critical time (tc) for cases (627 days), deaths (389 days), and people vaccinated (268 days), which led to the maximum speed values on those days. Negative correlations were identified between people vaccinated and cases (-0.40) and between people vaccinated and deaths (-0.75), suggesting reciprocal relationships between those pairs of variables. In addition, Granger causality tests determined that the vaccinated population dynamics can be used to forecast the behavior of deaths (p-value < 0.05), evidencing the impact of vaccinations against COVID-19. Also, the coefficient of determination (R2) indicated a robust representation of the real data. Using the Peruvian context as an example case, the logistic model's projections of cases, deaths, and vaccinations provide crucial insights into the pandemic, guiding public health tactics and reaffirming the essential role of vaccinations and resource distribution for an effective fight against COVID-19.

Genomic characterization of SARS-CoV-2 from an indigenous reserve in Mato Grosso do Sul, Brazil

Background

The COVID-19 pandemic had a major impact on indigenous populations. Understanding the viral dynamics within this population is essential to create targeted protection measures.

Methods

A total of 204 SARS-CoV-2 positive samples collected between May 2020 and November 2021 from an indigenous area in Mato Grosso do Sul (MS), Midwestern Brazil, were screened. Samples were submitted to whole genome sequencing using the Nanopore sequencing platform. Clinical, demographic, and phylogenetic data were analyzed.

Results

We found the co-circulation of six main SARS-CoV-2 lineages in the indigenous population, with the Zeta lineage being the most prevalent (27.66%), followed by B.1.1 (an ancestral strain) (20.21%), Gamma (14.36%) and Delta (13.83%). Other lineages represent 45.74% of the total. Our phylogenetic reconstruction indicates that multiple introduction events of different SARS-CoV-2 lineages occurred in the indigenous villages in MS. The estimated indigenous population mortality rate was 1.47%. Regarding the ethnicity of our cohort, 64.82% belong to the Guarani ethnicity, while 33.16% belong to the Terena ethnicity, with a slightly higher prevalence of males (53.43%) among females. Other ethnicities represent 2.01%. We also observed that almost all patients (89.55%) presented signs and symptoms related to COVID-19, being the most prevalent cough, fever, sore throat, and headache.

Discussion

Our results revealed that multiple independent SARS-CoV-2 introduction events had occurred through time, probably due to indigenous mobility, since the villages studied here are close to urban areas in MS. The mortality rate was slightly below of the estimation for the state in the period studied, which we believe could be related to the small number of samples evaluated, the underreporting of cases and deaths among this population, and the inconsistency of secondary data available for this study.

Conclusion

In this study, we showed the circulation of multiple SARS-CoV-2 variants in this population, which should be isolated and protected as they belong to the most fragile group due to their socioeconomic and cultural disparities. We reinforce the need for constant genomic surveillance to monitor and prevent the spread of new emerging viruses and to better understand the viral dynamics in these populations, making it possible to direct specific actions.

Policy responses to COVID-19 in Sri Lanka and the consideration of Indigenous Peoples

COVID-19 has had uneven impacts on health and well-being, with Indigenous communities in the Global South facing some of the highest risks. Focusing on the experience of Sri Lanka, this study identifies key policy responses to COVID-19, documents how they evolved over two years of the pandemic, and examines if and how government responses have addressed issues pertaining to Indigenous Peoples. Drawing upon an analysis of policy documents (n = 110) and interviews with policymakers (n = 20), we characterize seven key policy responses implemented by the Sri Lankan government: i) testing for and identifying COVID-19; ii) quarantine procedures; iii) provisional clinical treatments; iv) handling other diseases during COVID-19; v) movement; vi) guidelines to be adhered to by the general public; and vii) health and vaccination. The nature of these responses changed as the pandemic progressed. There is no evidence that policy development or implementation incorporated the voices and needs of Indigenous Peoples.

COVID-19 contagion across remote communities in tropical forests

Understanding COVID-19 contagion among poor populations is hampered by a paucity of data, and especially so in remote rural communities with limited access to transportation, communication, and health services. We report on the first study on COVID-19 contagion across rural communities without road access. We conducted telephone surveys with over 400 riverine communities in the Peruvian Amazon in the early phase of the pandemic. During the first wave (April-June, 2020), COVID-19 spread from cities to most communities through public and private river transportation according to their remoteness. The initial spread was delayed by transportation restrictions but at the same time was driven in unintended ways by government social assistance. During the second wave (August, 2020), although people's self-protective behaviors (promoted through communication access) helped to suppress the contagion, people responded to transportation restrictions and social assistance in distinct ways, leading to greater contagion among Indigenous communities than mestizo communities. As such, the spatial contagion during the early phase of the pandemic in tropical forests was shaped by river transportation and social behaviors. These novel findings have important implications for research and policies on pandemics in rural areas.