Etiology of acute febrile illness in the peruvian amazon as determined by modular formatted quantitative PCR: a protocol for RIVERA, a health facility-based case-control study.

BACKGROUND: The study of the etiology of acute febrile illness (AFI) has historically been designed as a prevalence of pathogens detected from a case series. This strategy has an inherent unrealistic assumption that all pathogen detection allows for causal attribution, despite known asymptomatic carriage of the principal causes of acute febrile illness in most low- and middle-income countries (LMICs). We designed a semi-quantitative PCR in a modular format to detect bloodborne agents of acute febrile illness that encompassed common etiologies of AFI in the region, etiologies of recent epidemics, etiologies that require an immediate public health response and additional pathogens of unknown endemicity. We then designed a study that would delineate background levels of transmission in the community in the absence of symptoms to provide corrected estimates of attribution for the principal determinants of AFI. METHODS: A case-control study of acute febrile illness in patients ten years or older seeking health care in Iquitos, Loreto, Peru, was planned. Upon enrollment, we will obtain blood, saliva, and mid-turbinate nasal swabs at enrollment with a follow-up visit on day 21-28 following enrollment to attain vital status and convalescent saliva and blood samples, as well as a questionnaire including clinical, socio-demographic, occupational, travel, and animal contact information for each participant. Whole blood samples are to be simultaneously tested for 32 pathogens using TaqMan array cards. Mid-turbinate samples will be tested for SARS-CoV-2, Influenza A and Influenza B. Conditional logistic regression models will be fitted treating case/control status as the outcome and with pathogen-specific sample positivity as predictors to attain estimates of attributable pathogen fractions for AFI. DISCUSSION: The modular PCR platforms will allow for reporting of all primary results of respiratory samples within 72 h and blood samples within one week, allowing for results to influence local medical practice and enable timely public health responses. The inclusion of controls will allow for a more accurate estimate of the importance of specific prevalent pathogens as a cause of acute illness. STUDY REGISTRATION: Project 1791, Registro de Proyectos de Investigación en Salud Pública (PRISA), Instituto Nacional de Salud, Perú.

[Epidemiological profile of extensively drug-resistant tuberculosis in Peru, 2013-2015Perfil epidemiológico da tuberculose extremamente resistente no Peru, 2013-2015]. / Perfil epidemiológico de la tuberculosis extensivamente resistente en el Perú, 2013-2015.

OBJECTIVE: Describe the clinical and epidemiological characteristics and resistance profile of cases of extensively drug-resistant tuberculosis (XDR-TB) diagnosed in Peru from 2013 to 2015. METHODS: This descriptive study included patients who met the definition of XDR-TB and were reported to the national epidemiological surveillance system of Peru's Ministry of Health. It used a descriptive analysis and, to identify spatial distribution, a heat map based on kernel density estimation. RESULTS: It was estimated that XDR-TB cases diagnosed as new represented 7.3% of all multidrug-resistant tuberculosis (MDR-TB) cases reported during the study period; 74% of patients were aged 15 to 44 years old; and the male-female ratio was 1.7. Half of the country's departments reported at least one case of XDR-TB, and 42% of new cases had no history of resistance or previous treatment. In the other half of the departments, the majority had previous MDR and pre-XDR resistance. Among the cases, 57.7% presented resistance to 5 and 7 first- and second-line drugs and 41.6% presented resistance to 8 and 10 drugs. CONCLUSIONS: This study offers important details of the epidemiological profile of XDR-TB in Peru, where there has been an increase in cases of primary XDR-TB; that is, cases with no prior history of disease. Furthermore, this form of tuberculosis has spread to a greater number of departments in the country.

OBJETIVO: Descrever as características clínico-epidemiológicas e o perfil de resistência dos casos de tuberculose extremamente resistente (TB-XDR) diagnosticados no Peru entre 2013 e 2015. MÉTODOS: Estudo descritivo que incluiu pacientes que cumpriam a definição de TB-XDR e foram notificados ao sistema nacional de vigilância epidemiológica do Ministério da Saúde do Peru. Foi realizada uma análise descritiva e elaborado um mapa de calor (heat map) com base na estimativa de densidade de Kernel para identificar a distribuição espacial. RESULTADOS: Estimou-se que os casos de TB-XDR diagnosticados como novos representaram 7,3% do número total de casos de tuberculose multidrogarresistente (TB-MDR) notificados no período do estudo, 74% dos casos tiveram entre 15 e 44 anos de idade, e a relação homem/mulher foi de 1,7. A metade dos departamentos notificou pelo menos um caso de TB-XDR, e 42% dos casos novos não tinham histórico de resistência ou tratamento prévio. Na outra metade dos departamentos, a maioria tinha resistência prévia do tipo MDR e pré-XDR. Ao todo, 57,7% dos casos apresentaram resistência a 5 e 7 medicamentos e 41,6% apresentaram resistência a 8 e 10 medicamentos de primeira e segunda linha. CONCLUSÕES: Este estudo apresenta detalhes importantes do perfil epidemiológico da TB-XDR no Peru, onde se observa um aumento no número de casos de TB-XDR primária, isto é, casos sem histórico de doença anterior. Além disso, esta forma de TB estendeu-se a um maior número de departamentos do país.

High altitudes, population density, and poverty: Unraveling the complexities of COVID-19 in Peru during the years 2020-2022.

Background: Several factors related to hospitalizations, morbidity, and mortality from COVID-19 have been identified. However, limited exploration has been done on geographic and socioeconomic factors that could significantly impact these outcomes. Objectives: This study aimed to determine whether altitude, population density, and percentage of population in total poverty are associated with COVID-19 incidence per 1000 inhabitants and COVID-19 case-fatality rate in Peru, from 2020 to 2022. Methods: This study utilized a multiple group ecological design and relied on secondary databases containing daily records of COVID-19 positive cases and deaths due to COVID-19. An epidemiological analysis was performed, subsequently processed using a random effects model. Results: As of August 2022, Peru had recorded a total of 3,838,028 COVID-19 positive cases and 215,023 deaths due to COVID-19. Our analysis revealed a statistically significant negative association between altitude and COVID-19 incidence (aBETA: -0.004; Standard Error: 0.001; p < 0.05). Moreover, we observed a positive association between population density and incidence (aBETA: 0.006; Standard Error: 0.001; p < 0.05). However, we found no significant association between the percentage of population in total poverty and COVID-19 incidence. Conclusion: Our study found that an increase in altitude was associated with a decrease in COVID-19 incidence, while an increase in population density was associated with an increase in COVID-19 incidence. High altitude, population density and percentage of population in total poverty does not change case-fatality rate due to COVID-19.

Etiology of Acute Febrile Illness in the Peruvian Amazon as determined by modular formatted quantitative PCR: A Protocol for RIVERA, a Health Facility-Based Case-Control Study.

Background: The study of the etiology of acute febrile illness (AFI) has historically been designed as a prevalence of pathogens detected from a case series. This strategy has an inherent unrealistic assumption that all pathogen detection allows for causal attribution, despite known asymptomatic carriage of the principal causes of acute febrile illness in most low- and middle-income countries (LMICs). We designed a semi-quantitative PCR in a modular format to detect bloodborne agents of acute febrile illness that encompassed common etiologies of AFI in the region, etiologies of recent epidemics, etiologies that require an immediate public health response and additional pathogens of unknown endemicity. We then designed a study that would delineate background levels of transmission in the community in the absence of symptoms to provide corrected estimates of attribution for the principal determinants of AFI. Methods: A case-control study of acute febrile illness in patients ten years or older seeking health care in Iquitos, Loreto, Peru, was planned. Upon enrollment, we will obtain blood, saliva, and mid-turbinate nasal swabs at enrollment with a follow-up visit on day 21-28 following enrollment to attain vital status and convalescent saliva and blood samples, as well as a questionnaire including clinical, socio-demographic, occupational, travel, and animal contact information for each participant. Whole blood samples are to be simultaneously tested for 32 pathogens using TaqMan array cards. Mid-turbinate samples will be tested for SARS-CoV-2, Influenza A and Influenza B. Conditional logistic regression models will be fitted treating case/control status as the outcome and with pathogen-specific sample positivity as predictors to attain estimates of attributable pathogen fractions for AFI. Discussion: The modular PCR platforms will allow for reporting of all primary results of respiratory samples within 72 hours and blood samples within one week, allowing for results to influence local medical practice and enable timely public health responses. The inclusion of controls will allow for a more accurate estimate of the importance of specific, prevalent pathogens as a cause of acute illness. Study Registration: Project 1791, Registro de Proyectos de Investigación en Salud Pública (PRISA), Instituto Nacional de Salud, Perú.

[Prevalence of latent tuberculosis infection in health workers from primary health care centers in Lima, Peru]. / Prevalencia de infección tuberculosa latente en trabajadores de salud de establecimientos del primer nivel de atención. Lima, Perú.

To evaluate the risk of tuberculosis (TB) infection, the General Directorate of Epidemiology of the Ministry of Health developed a sentinel surveillance system in health centers located in the Constitutional Province of Callao. This surveillance system included the diagnosis of latent tuberculosis infection (LTI) using interferon gamma release assays. The objective of the present study was to estimate the prevalence of LTI in health workers in a region with a high burden of TB. The prevalence of LTI in health workers was 56%. The prevalence of LTI was 63% in workers with more than 10 years of service and 58-60% in workers with more than 35 years of service. The prevalence of LTI in health workers from primary health care centers was high, and longer service time was one of the main risk factors.

Con el propósito de disponer de información sobre los riesgos para infección por tuberculosis, la Dirección General de Epidemiología del Ministerio de Salud, desarrolló una vigilancia centinela en establecimientos de salud de la Provincia constitucional del Callao, dicha vigilancia incluyó el diagnóstico de infección tuberculosa latente (ITL) mediante la aplicación del método IGRA. El objetivo del presente estudio fue estimar la prevalencia de ITL en trabajadores de salud de un área con alta carga de enfermedad de tuberculosis. La prevalencia de ITL en trabajadores de salud fue 56%. En trabajadores con más de 10 años de servicio la prevalencia se incrementó a 63% y en trabajadores con más de 35 años de servicio se encontraron prevalencias entre 58 y 60%. Existe una alta prevalencia de ITL en trabajadores de salud de establecimientos del primer nivel de atención, identificándose al mayor tiempo de servicio, como uno de los principales factores de riesgo.

Perfil epidemiológico de la tuberculosis extensivamente resistente en el Perú, 2013-2015

[RESUMEN]. Objetivo. Describir las características clínico-epidemiológicas y el perfil de resistencia de los casos de tuberculosis extensivamente resistente (TB-XDR) diagnosticados en Perú entre los años 2013 y 2015. Métodos. Estudio descriptivo que incluyó a los pacientes que cumplían con la definición de TB-XDR y que fueron notificados al sistema nacional de vigilancia epidemiológica del Ministerio de Salud del Perú. Se realizó un análisis descriptivo y se elaboró un mapa de calor basado en la estimación de densidad Kernel para identificar la distribución espacial. Resultados. Se estimó que los casos de TB-XDR diagnosticados como nuevos representaron 7,3% del total de casos de tuberculosis multidrogorresistente (TB-MDR) reportados para el período de estudio, 74% de los casos tenían entre 15 y 44 años y la relación hombre/mujer fue de 1,7. La mitad de los departamentos reportó al menos un caso de TB-XDR, con 42% de casos nuevos sin ningún antecedente de resistencia ni tratamiento previo. En la otra mitad de los departamentos, la mayoría tenían resistencia previa tipo MDR y de tipo pre-XDR. El 57,7% de los casos presentaron resistencia a 5 y 7 drogas y 41,6% presentaba resistencia a 8 y 10 drogas de primera y segunda línea. Conclusiones. Este estudio ofrece detalles importantes del perfil epidemiológico de la TB-XDR en el Perú, donde se muestra un incremento de los casos de TB-XDR primario; es decir, casos sin antecedentes de enfermedad previa. Además, esta forma de tuberculosis se ha extendido a un mayor número de departamentos del país.

[ABSTRACT]. Objective. Describe the clinical and epidemiological characteristics and resistance profile of cases of extensively drug-resistant tuberculosis (XDR-TB) diagnosed in Peru from 2013 to 2015. Methods. This descriptive study included patients who met the definition of XDR-TB and were reported to the national epidemiological surveillance system of Peru’s Ministry of Health. It used a descriptive analysis and, to identify spatial distribution, a heat map based on kernel density estimation. Results. It was estimated that XDR-TB cases diagnosed as new represented 7.3% of all multidrug-resistant tuberculosis (MDR-TB) cases reported during the study period; 74% of patients were aged 15 to 44 years old; and the male-female ratio was 1.7. Half of the country’s departments reported at least one case of XDR-TB, and 42% of new cases had no history of resistance or previous treatment. In the other half of the departments, the majority had previous MDR and pre-XDR resistance. Among the cases, 57.7% presented resistance to 5 and 7 first- and second-line drugs and 41.6% presented resistance to 8 and 10 drugs. Conclusions. This study offers important details of the epidemiological profile of XDR-TB in Peru, where there has been an increase in cases of primary XDR-TB; that is, cases with no prior history of disease. Furthermore, this form of tuberculosis has spread to a greater number of departments in the country.

[RESUMO]. Objetivo. Descrever as características clínico-epidemiológicas e o perfil de resistência dos casos de tuberculose extremamente resistente (TB-XDR) diagnosticados no Peru entre 2013 e 2015. Métodos. Estudo descritivo que incluiu pacientes que cumpriam a definição de TB-XDR e foram notificados ao sistema nacional de vigilância epidemiológica do Ministério da Saúde do Peru. Foi realizada uma análise descritiva e elaborado um mapa de calor (heat map) com base na estimativa de densidade de Kernel para identificar a distribuição espacial. Resultados. Estimou-se que os casos de TB-XDR diagnosticados como novos representaram 7,3% do número total de casos de tuberculose multidrogarresistente (TB-MDR) notificados no período do estudo, 74% dos casos tiveram entre 15 e 44 anos de idade, e a relação homem/mulher foi de 1,7. A metade dos departamentos notificou pelo menos um caso de TB-XDR, e 42% dos casos novos não tinham histórico de resistência ou tratamento prévio. Na outra metade dos departamentos, a maioria tinha resistência prévia do tipo MDR e pré-XDR. Ao todo, 57,7% dos casos apresentaram resistência a 5 e 7 medicamentos e 41,6% apresentaram resistência a 8 e 10 medicamentos de primeira e segunda linha. Conclusões. Este estudo apresenta detalhes importantes do perfil epidemiológico da TB-XDR no Peru, onde se observa um aumento no número de casos de TB-XDR primária, isto é, casos sem histórico de doença anterior. Além disso, esta forma de TB estendeu-se a um maior número de departamentos do país.

Prevalencia de infección tuberculosa latente en trabajadores de salud de establecimientos del primer nivel de atención. Lima, Perú / Prevalence of latent tuberculosis infection in health workers from primary health care centers in Lima, Peru

RESUMEN Con el propósito de disponer de información sobre los riesgos para infección por tuberculosis, la Dirección General de Epidemiología del Ministerio de Salud, desarrolló una vigilancia centinela en establecimientos de salud de la Provincia constitucional del Callao, dicha vigilancia incluyó el diagnóstico de infección tuberculosa latente (ITL) mediante la aplicación del método IGRA. El objetivo del presente estudio fue estimar la prevalencia de ITL en trabajadores de salud de un área con alta carga de enfermedad de tuberculosis. La prevalencia de ITL en trabajadores de salud fue 56%. En trabajadores con más de 10 años de servicio la prevalencia se incrementó a 63% y en trabajadores con más de 35 años de servicio se encontraron prevalencias entre 58 y 60%. Existe una alta prevalencia de ITL en trabajadores de salud de establecimientos del primer nivel de atención, identificándose al mayor tiempo de servicio, como uno de los principales factores de riesgo.

ABSTRACT To evaluate the risk of tuberculosis (TB) infection, the General Directorate of Epidemiology of the Ministry of Health developed a sentinel surveillance system in health centers located in the Constitutional Province of Callao. This surveillance system included the diagnosis of latent tuberculosis infection (LTI) using interferon gamma release assays. The objective of the present study was to estimate the prevalence of LTI in health workers in a region with a high burden of TB. The prevalence of LTI in health workers was 56%. The prevalence of LTI was 63% in workers with more than 10 years of service and 58-60% in workers with more than 35 years of service. The prevalence of LTI in health workers from primary health care centers was high, and longer service time was one of the main risk factors.

Statistical analyses in disease surveillance systems.

The performance of disease surveillance systems is evaluated and monitored using a diverse set of statistical analyses throughout each stage of surveillance implementation. An overview of their main elements is presented, with a specific emphasis on syndromic surveillance directed to outbreak detection in resource-limited settings. Statistical analyses are proposed for three implementation stages: planning, early implementation, and consolidation. Data sources and collection procedures are described for each analysis.During the planning and pilot stages, we propose to estimate the average data collection, data entry and data distribution time. This information can be collected by surveillance systems themselves or through specially designed surveys. During the initial implementation stage, epidemiologists should study the completeness and timeliness of the reporting, and describe thoroughly the population surveyed and the epidemiology of the health events recorded. Additional data collection processes or external data streams are often necessary to assess reporting completeness and other indicators. Once data collection processes are operating in a timely and stable manner, analyses of surveillance data should expand to establish baseline rates and detect aberrations. External investigations can be used to evaluate whether abnormally increased case frequency corresponds to a true outbreak, and thereby establish the sensitivity and specificity of aberration detection algorithms.Statistical methods for disease surveillance have focused mainly on the performance of outbreak detection algorithms without sufficient attention to the data quality and representativeness, two factors that are especially important in developing countries. It is important to assess data quality at each state of implementation using a diverse mix of data sources and analytical methods. Careful, close monitoring of selected indicators is needed to evaluate whether systems are reaching their proposed goals at each stage.