Nucleic acid based point-of-care diagnostic technology for infectious disease detection using machine learning empowered smartphone-interfaced quantitative colorimetry.

We report a nucleic acid-based point of care testing technology for infectious disease detection at resource limited settings by integrating a low-cost portable device with machine learning-empowered quantitative colorimetric analytics that can be interfaced via a smartphone application. We substantiate our proposition by demonstrating the efficacy of this technology in detecting COVID-19 infection from human swab samples, using the RT-LAMP protocol. Comparison with gold standard results from real-time PCR evidences high sensitivity and specificity, ensuring simplicity, portability, and user-friendliness of the technology at the same time. Colorimetric analytics of the reaction output without necessitating the opening of the reaction microchambers enables execution of the complete test workflow without any laboratory control that may otherwise be required stringently for safeguarding against carryover contamination. Seamless sample-to-answer workflow and machine learning-based readout further assures minimal human intervention for the test readout, thus eliminating inevitable inaccuracies stemming from erroneous execution of the test as well as subjectivity in interpreting the outcome. Our results further indicate the possibilities of upgrading the technology to predict the pathogenic load on the infected patients akin to the cyclic threshold value of the real-time PCR, when calibrated with reference to a wide range of 'training' data for the machine learner, thereby putting forward the same as viable alternative to the resource-intensive PCR tests that cannot be made readily accessible at underserved community settings.

IL-10/IL-6 ratio from nasal & oral swab samples, acts as an inflammatory indicator for COVID-19 patients infected with the delta variant.

Background: Hyper-inflammatory immune response of SARS-CoV-2 is often characterized by the release of multiple pro-inflammatory cytokines with an impact on the expression of numerous other interleukins (ILs). However, from oral and nasal swab samples the specific quantitative association of the different IL-markers with the disease progression and its relationship with the status of vaccination remains unclear. Materials and methods: Patients' combined oral and nasal swab samples were collected from both non-vaccinated and double-vaccinated individuals with high (Ct value < 25) and low (Ct value > 30) viral loads, along with uninfected donors. None of the patients were critically ill, or needed ICU support. The expression of different cytokines (IL6, IL10, IL1B, IFNG) and mucin (MUC5AC, MUC1) markers were assessed between different groups by qRT-PCR. The important cytokine markers differentiating between vaccinated and non-vaccinated patients were identified by PCA. Conclusion: IL6 expression was higher in non-vaccinated COVID-19 patients infected with delta-variant irrespective of their viral-load compared to uninfected individuals. However, in double-vaccinated patients, only in high viral-load patients (Ct value < 25), IL6 expression increased. In high viral-load patients, irrespective to their vaccination status, IL10 expression was lower compared to the uninfected control group. Surprisingly, IL10 expression was lower in double-vaccinated patients with Ct value > 30. IL1B, and IFNG expression remained unaltered in uninfected and infected individuals. However, MUC5AC expression was lower in non-vaccinated patients with Ct value < 25 compared to control group. Our study unveiled that IL10/IL6 ratio can be used as a biomarker for COVID-19 patients upon proper establishment of it in a clinical setting.

Piecewise Isothermal Nucleic Acid Testing (PINAT) for Infectious Disease Detection with Sample-to-Result Integration at the Point-of-Care.

We developed a piecewise isothermal nucleic acid test (PINAT) as a platform technology for diagnosing pathogen-associated infections, empowered by an illustrative novel methodology that embeds an exclusive DNA-mediated specific probing reaction with the backbone of an isothermal reverse transcription cum amplification protocol for detecting viral RNA. In a point-of-care format, this test is executable in a unified single-step, single-chamber procedure, leading to seamless sample-to-result integration in an inexpensive, scalable, pre-programmable, and customizable portable device, with mobile-app-integrated interpretation and analytics involving minimal manually operative procedures. The test exhibited a high sensitivity and specificity of detection when assessed using 200 double-blind patient samples for detecting SARS-CoV-2 infection by the Indian Council of Medical Research (ICMR), and subsequently using 170 double-blind patient samples in a point-of-care format outside controlled laboratory settings as performed by unskilled technicians in an organized clinical trial. We also established its efficacy in detecting Influenza A infection by performing the diagnosis at the point of collection with uncompromised detection rigor. The envisaged trade-off between advanced laboratory-based molecular diagnostic procedures and the elegance of common rapid tests renders the method ideal for deployment in resource-limited settings towards catering the needs of the underserved.

Optimizing Village-Level Targeting of Active Case Detection to Support Visceral Leishmaniasis Elimination in India.

Background: India has made major progress in improving control of visceral leishmaniasis (VL) in recent years, in part through shortening the time infectious patients remain untreated. Active case detection decreases the time from VL onset to diagnosis and treatment, but requires substantial human resources. Targeting approaches are therefore essential to feasibility. Methods: We analyzed data from the Kala-azar Management Information System (KAMIS), using village-level VL cases over specific time intervals to predict risk in subsequent years. We also graphed the time between cases in villages and examined how these patterns track with village-level risk of additional cases across the range of cumulative village case-loads. Finally, we assessed the trade-off between ACD effort and yield. Results: In 2013, only 9.3% of all villages reported VL cases; this proportion shrank to 3.9% in 2019. Newly affected villages as a percentage of all affected villages decreased from 54.3% in 2014 to 23.5% in 2019, as more surveillance data accumulated and overall VL incidence declined. The risk of additional cases in a village increased with increasing cumulative incidence, reaching approximately 90% in villages with 12 cases and 100% in villages with 45 cases, but the vast majority of villages had small cumulative case numbers. The time-to-next-case decreased with increasing case-load. Using a 3-year window (2016-2018), a threshold of seven VL cases at the village level selects 329 villages and yields 23% of cases reported in 2019, while a threshold of three cases selects 1,241 villages and yields 46% of cases reported in 2019. Using a 6-year window increases both effort and yield. Conclusion: Decisions on targeting must consider the trade-off between number of villages targeted and yield and will depend upon the operational efficiencies of existing programs and the feasibility of specific ACD approaches. The maintenance of a sensitive, comprehensive VL surveillance system will be crucial to preventing future VL resurgence.

Development and Evaluation of Active Case Detection Methods to Support Visceral Leishmaniasis Elimination in India.

As India moves toward the elimination of visceral leishmaniasis (VL) as a public health problem, comprehensive timely case detection has become increasingly important, in order to reduce the period of infectivity and control outbreaks. During the 2000s, localized research studies suggested that a large percentage of VL cases were never reported in government data. However, assessments conducted from 2013 to 2015 indicated that 85% or more of confirmed cases were eventually captured and reported in surveillance data, albeit with significant delays before diagnosis. Based on methods developed during these assessments, the CARE India team evolved new strategies for active case detection (ACD), applicable at large scale while being sufficiently effective in reducing time to diagnosis. Active case searches are triggered by the report of a confirmed VL case, and comprise two major search mechanisms: 1) case identification based on the index case's knowledge of other known VL cases and searches in nearby houses (snowballing); and 2) sustained contact over time with a range of private providers, both formal and informal. Simultaneously, house-to-house searches were conducted in 142 villages of 47 blocks during this period. We analyzed data from 5030 VL patients reported in Bihar from January 2018 through July 2019. Of these 3033 were detected passively and 1997 via ACD (15 (0.8%) via house-to-house and 1982 (99.2%) by light touch ACD methods). We constructed multinomial logistic regression models comparing time intervals to diagnosis (30-59, 60-89 and ≥90 days with <30 days as the referent). ACD and younger age were associated with shorter time to diagnosis, while male sex and HIV infection were associated with longer illness durations. The advantage of ACD over PCD was more marked for longer illness durations: the adjusted odds ratios for having illness durations of 30-59, 60-89 and >=90 days compared to the referent of <30 days for ACD vs PCD were 0.88, 0.56 and 0.42 respectively. These ACD strategies not only reduce time to diagnosis, and thus risk of transmission, but also ensure that there is a double check on the proportion of cases actually getting captured. Such a process can supplement passive case detection efforts that must go on, possibly perpetually, even after elimination as a public health problem is achieved.

Variations in visceral leishmaniasis burden, mortality and the pathway to care within Bihar, India.

BACKGROUND: Visceral leishmaniasis (VL) has been targeted by the WHO for elimination as a public health problem (< 1 case/10,000 people/year) in the Indian sub-continent (ISC) by 2020. Bihar State in India, which accounts for the majority of cases in the ISC, remains a major target for this elimination effort. However, there is considerable spatial, temporal and sub-population variation in occurrence of the disease and the pathway to care, which is largely unexplored and a threat to achieving the target. METHODS: Data from 6081 suspected VL patients who reported being clinically diagnosed during 2012-2013 across eight districts in Bihar were analysed. Graphical comparisons and Chi-square tests were used to determine differences in the burden of identified cases by season, district, age and sex. Log-linear regression models were fitted to onset (of symptoms)-to-diagnosis and onset-to-treatment waiting times to estimate their associations with age, sex, district and various socio-economic factors (SEFs). Logistic regression models were used to identify factors associated with mortality. RESULTS: Comparisons of VL caseloads suggested an annual cycle peaking in January-March. A 17-fold variation in the burden of identified cases across districts and under-representation of young children (0-5 years) relative to age-specific populations in Bihar were observed. Women accounted for a significantly lower proportion of the reported cases than men (41 vs 59%, P < 0.0001). Age, district of residence, house wall materials, caste, treatment cost, travelling for diagnosis and the number of treatments for symptoms before diagnosis were identified as correlates of waiting times. Mortality was associated with age, district of residence, onset-to-treatment waiting time, treatment duration, cattle ownership and cost of diagnosis. CONCLUSIONS: The distribution of VL in Bihar is highly heterogeneous, and reported caseloads and associated mortality vary significantly across different districts, posing different challenges to the elimination campaign. Socio-economic factors are important correlates of these differences, suggesting that elimination will require tailoring to population and sub-population circumstances.

Epidemiologic Correlates of Mortality among Symptomatic Visceral Leishmaniasis Cases: Findings from Situation Assessment in High Endemic Foci in India.

BACKGROUND: Visceral leishmaniasis (VL) is highly prevalent in the Indian state of Bihar and, without proper diagnosis and treatment, is associated with high fatality. However, lack of efficient reporting mechanism had been an impediment in estimating the burden of mortality and its antecedents among symptomatic VL cases. The objectives of the current study were to generate a reliable estimate of symptomatic VL caseload and mortality in Bihar, as well as to identify the epidemiologic and health infrastructure-related predictors of VL mortality. METHODOLOGY AND PRINCIPAL FINDINGS: Using an elaborate index case tracing method, we attempted to locate all symptomatic VL patients in eight districts of Bihar. Interviews and medical-record-reviews were conducted with cases (or next-of-kin for the dead) meeting the eligibility criteria. The information collected during the interviews included socio-demographic characteristics, onset of disease symptoms, place of diagnosis, pre- and post-diagnosis treatment history, type and duration of drugs received. In total, we analyzed data on 4925 VL patients-59% were male and 68% were less than 30 years old. There were 158 (3.2%) deaths and the incidence rate of mortality was 3.2/100 person-years. In the adjusted Cox-proportional-hazards analysis, treatment at public facility [Adjusted Hazard Ratio (AHR) = 0.61; 95% CI = 0.43-0.86], shorter (≤30 days) diagnostic delay [AHR = 0.62, 95% CI = 0.43-0.92], and treatment completion [AHR = 0.03, 95% CI = 0.02-0.05] emerged as significant negative predictors of mortality. CONCLUSION: Mortality reduction efforts in Bihar should focus on improving access to early diagnosis, quality treatment and treatment-adherence measures, with special emphasis on marginalized communities.