A Cross-Sectional Study of Seroprevalence of Strongyloidiasis in Pregnant Women (Peruvian Amazon Basin).

Strongyloidiasis is a soil-transmitted helminthiasis with a high global prevalence. OBJECTIVES: We aimed to evaluate the prevalence of Strongyloides stercoralis infection and assess strongyloidiasis serology as a screening technique in the Peruvian Amazon. MATERIAL AND METHODS: We performed a cross-sectional study of strongyloidiasis in 300 pregnant women in Iquitos (Peru) from 1 May 2019 to 15 June 2019. Women were tested using serology (Strongyloides IgG IVD-ELISA kit) as an index test and the modified Baermann technique and/or charcoal fecal culture as the parasitological reference standard. RESULTS: The reference tests showed S. stercoralis in the stool of 30 women (prevalence: 10%; 95% confidence interval [CI] 7.1% to 13.9%), while 101 women tested positive on the blood test (prevalence: 33.7%; 95% CI 28.6% to 39.4%). Fourteen of the 15 women (93.3%) with positive results according to the modified Baermann technique, and 14 of the 23 women (56.5%) with positive charcoal cultures also had positive serological results. Serology showed a sensitivity of 63.3% and a negative predictive value of 94.4%. CONCLUSION: In Iquitos, pregnant women have a high prevalence of S stercoralis. S. stercoralis ELISA could be an excellent tool for population-based screening, as it has a high negative predictive value that can help to rule out the presence of active infection.

Microsatellite analysis reveals connectivity among geographically distant transmission zones of Plasmodium vivax in the Peruvian Amazon: A critical barrier to regional malaria elimination.

Despite efforts made over decades by the Peruvian government to eliminate malaria, Plasmodium vivax remains a challenge for public health decision-makers in the country. The uneven distribution of its incidence, plus its complex pattern of dispersion, has made ineffective control measures based on global information that lack the necessary detail to understand transmission fully. In this sense, population genetic tools can complement current surveillance. This study describes the genetic diversity and population structure from September 2012 to March 2015 in three geographically distant settlements, Cahuide (CAH), Lupuna (LUP) and Santa Emilia (STE), located in the Peruvian Amazon. A total 777 P. vivax mono-infections, out of 3264, were genotyped. Among study areas, LUP showed 19.7% of polyclonal infections, and its genetic diversity (Hexp) was 0.544. Temporal analysis showed a significant increment of polyclonal infections and Hexp, and the introduction and persistence of a new parasite population since March 2013. In STE, 40.1% of infections were polyclonal, with Hexp = 0.596. The presence of four genetic clusters without signals of clonal expansion and infections with lower parasite densities compared against the other two areas were also found. At least four parasite populations were present in CAH in 2012, where, after June 2014, malaria cases decreased from 213 to 61, concomitant with a decrease in polyclonal infections (from 0.286 to 0.18), and expectedly variable Hexp. Strong signals of gene flow were present in the study areas and wide geographic distribution of highly diverse parasite populations were found. This study suggests that movement of malaria parasites by human reservoirs connects geographically distant malaria transmission areas in the Peruvian Amazon. The maintenance of high levels of parasite genetic diversity through human mobility is a critical barrier to malaria elimination in this region.

Automated microscopy for routine malaria diagnosis: a field comparison on Giemsa-stained blood films in Peru.

BACKGROUND: Microscopic examination of Giemsa-stained blood films remains a major form of diagnosis in malaria case management, and is a reference standard for research. However, as with other visualization-based diagnoses, accuracy depends on individual technician performance, making standardization difficult and reliability poor. Automated image recognition based on machine-learning, utilizing convolutional neural networks, offers potential to overcome these drawbacks. A prototype digital microscope device employing an algorithm based on machine-learning, the Autoscope, was assessed for its potential in malaria microscopy. Autoscope was tested in the Iquitos region of Peru in 2016 at two peripheral health facilities, with routine microscopy and PCR as reference standards. The main outcome measures include sensitivity and specificity of diagnosis of malaria from Giemsa-stained blood films, using PCR as reference. METHODS: A cross-sectional, observational trial was conducted at two peripheral primary health facilities in Peru. 700 participants were enrolled with the criteria: (1) age between 5 and 75 years, (2) history of fever in the last 3 days or elevated temperature on admission, (3) informed consent. The main outcome measures included sensitivity and specificity of diagnosis of malaria from Giemsa-stained blood films, using PCR as reference. RESULTS: At the San Juan clinic, sensitivity of Autoscope for diagnosing malaria was 72% (95% CI 64-80%), and specificity was 85% (95% CI 79-90%). Microscopy performance was similar to Autoscope, with sensitivity 68% (95% CI 59-76%) and specificity 100% (95% CI 98-100%). At San Juan, 85% of prepared slides had a minimum of 600 WBCs imaged, thus meeting Autoscope's design assumptions. At the second clinic, Santa Clara, the sensitivity of Autoscope was 52% (95% CI 44-60%) and specificity was 70% (95% CI 64-76%). Microscopy performance at Santa Clara was 42% (95% CI 34-51) and specificity was 97% (95% CI 94-99). Only 39% of slides from Santa Clara met Autoscope's design assumptions regarding WBCs imaged. CONCLUSIONS: Autoscope's diagnostic performance was on par with routine microscopy when slides had adequate blood volume to meet its design assumptions, as represented by results from the San Juan clinic. Autoscope's diagnostic performance was poorer than routine microscopy on slides from the Santa Clara clinic, which generated slides with lower blood volumes. Results of the study reflect both the potential for artificial intelligence to perform tasks currently conducted by highly-trained experts, and the challenges of replicating the adaptiveness of human thought processes.