Pilot Study: Foldscope & Microfluidics

Title: Foldscope & Microfluidics: Accessible Diagnostics for Community-led Schistosomiasis Control

Collaborators/Co-Investigators & Institutional Affiliation:

Heath in Your Hands Team

Dr. Olubodun - Federal Medical Center Abeokuta, Ogun State (Senior Investigator)

Dr. Adebayo - Federal Medical Center Abeokuta, Ogun State

Dr. Adedayo - Federal Medical Center Abeokuta, Ogun State

Dr. Ekpo - Federal University of Agriculture, Abeokuta (FUNAAB), Nigeria

Dr. Oluwole - Sightsavers

Dr. Mogaji - Federal University Oye-Ekiti, Nigeria

Dr. Stafford - UTHealth Science Center at Houston

Dr. Lee - UTHealth Science Center at Houston

Dr. Tebo - UTHealth Science Center at Houston

Dr. Prakash - Stanford University, Foldscope Instruments

Dr. Cybulski - Stanford University, Foldscope Instruments

Dr. Moreno-Roman - Stanford University, Foldscope Instruments

  • Students, lab techs, and everybody involved will be listed accordingly

List of Abbreviations

CHEW: Community Health Extension Worker

FGD: Focus Group Discussion

FGS: Female Genital Schistosomiasis

HIYH: Health in Your Hands

HPV: Human Papillomavirus

KII: Key Informant Interview

LGA: Local Government Area

NPV: Negative Predictive Value

NTD: Neglected Tropical Disease

OGHREC: Ogun State Health Research Ethics Committee

PPV: Positive Predictive Value

WHO: World Health Organization

Protocol/Proposal Summary

This study aims to evaluate the effectiveness of the Foldscope, a low-cost paper microscope, for diagnosing Schistosoma haematobium in urine samples within rural Nigerian communities, particularly in rural Ogun state. The project will assess diagnostic accuracy, community acceptability, and feasibility of implementation through collaboration with local community health extension workers (CHEWs) and volunteers.

The study will compare Foldscope-based microscopy workflow with conventional methods, focusing on the effectiveness and accuracy of this diagnostic tool paired with a reusable microfluidic device for trapping eggs in urine. Additionally, we will measure feasibility and community acceptability using a mixed-methods approach including focus group discussions and key informant interviews.

The research will be conducted in selected rural communities near the Oyan River Dam in Ogun State, with a sample size of 365 participants. The study employs a cross-sectional design with both quantitative and qualitative components to evaluate the diagnostic tool's performance.

The expected benefit is the development of a sustainable, community-based diagnostic solution that could improve schistosomiasis surveillance in resource-limited settings, potentially transforming community-based disease detection and treatment strategies.

Chapter 1: Introduction

Background

Schistosomiasis is a significant public health issue in Nigeria, particularly in rural areas where access to diagnostics and treatment is limited by numerous barriers. Urogenital schistosomiasis is prevalent in rural areas where people rely on natural freshwater, with transmission depending on the abundance of the primary snail host (Ezeh et al., 2019). While Schistosoma haematobium infection is currently diagnosed mainly via traditional light microscope inspection of urine, the Foldscope presents an opportunity to provide low-cost, portable diagnostics, potentially transforming community-based disease detection and treatment strategies (Ephraim et al., 2015). However, there is a need to evaluate the use of the Foldscope for this purpose in the hands of community health extension workers (CHEWs) in rural settings, to better understand how this may be incorporated into control strategies. Additionally, there is no current suitable option for sample preparation that is cost-effective and does not require electricity. In the present study, we aim to fill these gaps in current knowledge.

Statement of the Problem

Studies have found the highest prevalence rates of schistosomiasis in school-aged children and young women, and high prevalence of urogenital schistosomiasis in Nigeria in many endemic states despite ongoing mass drug administration with praziquantel (Ezeh et al., 2019; Archer et al., 2024; Faust et al., 2021; Mtethiwa et al., 2015). Classic symptoms include hematuria, abdominal pain, and fatigue (WHO, 2023). Of particular concern is the development of female genital schistosomiasis (FGS), which can harm female reproductive organs and increase the risk for infertility, and HPV infection. FGS has been highly associated with bladder cancer, particularly squamous cell carcinoma and cervical cancer, which is associated with high rates of HPV infection in patients with FGS (Chatterji et al., 2024).

Geographical, financial, social and educational barriers currently prevent adequate diagnosis and screening in hyper-endemic (>50% endemicity) zones of schistosomiasis in Nigeria, including Ogun state (Ezeh et al., 2019). Traditional testing methods require trained personnel, costly lab equipment, and centralized facilities, making them less accessible. In rural communities, long travel distances to healthcare facilities and high costs associated with services deter individuals from seeking diagnosis (Van et al., 2020; Dawaki et al., 2015). This is exacerbated by limited awareness of schistosomiasis, limited recognition of the presenting symptoms by healthcare workers, as well as social stigma surrounding the presenting symptoms, leading to delays in seeking healthcare for those affected (Faust et al., 2020; Van et al., 2020; Dawaki et al., 2015). Local scholars point to a gap between policy-making and control measures for schistosomiasis, as well as a lack of clarity about the number of people affected by S. haematobium infection in endemic areas, making epidemiological data difficult to determine (Ezeh et al., 2019).

Justification/Significance of the Study

As schistosomiasis poses multifactorial challenges, a community-based, low-expense solution for diagnosing Schistosoma haematobium in urinary samples is needed. The project aims to work with local health workers in Foldscope-based microscopy, comparing its diagnostic accuracy, cost-effectiveness, and community acceptability to conventional microscopy methods. By empowering communities to diagnose schistosomiasis in a way that would reduce financial and travel barriers, this initiative aims to contribute to schistosomiasis control efforts.

We will also assess the use of a reusable microfluidic device capable of trapping Schistosoma haematobium eggs (Xiao et al., 2016) as the slide containing the urine sample, in order to evaluate the utility of trapping the eggs from urine mechanically as opposed to relying on centrifugation or expensive filtering, which relies on expensive equipment. To enhance the impact and scalability of this project, we aim to partner with national, state, and local leadership in Nigeria, and individuals already engaged in relevant public health and research initiatives, to build on existing work that has been done.

Our proposal is to evaluate the effectiveness of the Foldscope microscope and a microfluidic slide as diagnostic tools in Nigerian regions impacted by Schistosoma haematobium, starting with communities near the Oyan River Dam in Ogun State, where there is a recorded high-burden of this disease (Akinwale, 2010; Ekpo, 2012). Findings from this study could aid in further research to inform the development of scalable diagnostic strategies for rural settings incorporating accessible tools, communication, and education into control efforts.

Chapter 2: Research Objectives

2.1 General Objective

The central objective is to evaluate the use of Foldscope-based microscopy in an endemic area within a community of known high prevalence, comparing its diagnostic accuracy, cost-effectiveness, and community acceptability to conventional microscopy methods. With collaboration from local leadership, we aim to evaluate:

  • The effectiveness of the Foldscope (Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy)

  • Feasibility (using a mixed-methods approach)

  • Community acceptability & barriers of this Foldscope-based microscopy workflow in the diagnosis of genitourinary schistosomiasis caused by Schistosoma haematobium

2.2 Specific Objectives

  1. To determine the effectiveness of Foldscope microscopy for Schistosoma haematobium detection, as measured by sensitivity, specificity, PPV, NPV, and accuracy of this diagnostic tool, as well as the level of agreement between trained lab scientists and CHEWs using the Foldscope.

  2. To assess community feasibility of implementation, and opportunities for educational interventions for community health extension workers (CHEWs).

  3. To assess acceptability and barriers encountered using the Foldscope in this clinical setting vs. conventional methods, as measured by focused group discussions (FGDs), structured in-depth interviews, and key-informant interviews (KIIs) with community leaders and current control effort leaders. 

Chapter 3: Research Methods

3.1 Study Design

This is a mixed methods cross-sectional study aimed at evaluating Foldscope-based microscopy against conventional diagnostic methods. All samples will be examined with the current gold standard in addition to the experimental process. It will also incorporate qualitative research components to assess community perceptions and implementation feasibility.

3.2 Study Area

This study will be conducted in Ogun State, Nigeria, specifically within the Imala Odo and Imala communities near Oyan River Dam to begin with. These communities have been selected due to their varying prevalence rates of schistosomiasis, with Imala Odo showing high prevalence (greater than 90% from unpublished reports) and Imala showing decreasing prevalence. The study will be conducted in rural communities within two local government areas in Ogun State.

3.3 Study Population

The study will involve three distinct populations:

  1. Community members for diagnostic testing:

    • Individuals aged 5 years or older with a history of freshwater exposure, recent travel from endemic areas, or hematuria/urinary symptoms

    • Must be able to provide informed consent (or guardian consent for minors)

    • Capable of providing a urine sample of at least 30 mLs

  2. Healthcare workers for feasibility assessment:

    • Community health extension workers (CHEWs), lab scientists, technicians, nurses, or other clinicians

    • Willing to participate in both the diagnostic testing phase and the qualitative evaluation phase

  3. Key stakeholders for acceptability assessment:

    • Adults residing in rural communities in the study area

    • CHEWs or clinicians from the study communities

    • Other stakeholders with experience in schistosomiasis control (State & Local NTD coordinators, Medical Officers of Health, lab scientists or technicians)

    • Must have been involved with schistosomiasis control efforts in the past

3.4 Sample Size Determination

3.4.1 Diagnostic Accuracy Component

First, we assessed the current average prevalence of schistosomiasis in Oyan River Dam communities as 52% based on the existing literature (Akinwale, 2010; Ekpo, 2012). The formula for calculating the required sample size for sensitivity estimation in a diagnostic accuracy study was applied as follows, assuming a finite number of population of 1600 individuals since we are focusing on two communities with a limited population:

N =Z2* Se * (1-Se)d2 * P

Where:

  • N = Minimum required number of infected individuals

  • Z = Standard normal deviate corresponding to a 95% confidence level (1.96)

  • Se = Expected sensitivity of the diagnostic test (assumed 80% or 0.80)

  • d = Desired precision (5% or 0.05)

  • P = Prevalence of infection in the study population (52% or 0.=52)

Substituting values:

N =(1.96)2* 0.80* (1-0.80)(0.05)2 * 0.52

N 473

To adjusted for a finite population of 1600, we will apply to finite population correction:

Nadjusted =N1 + (N/ Npopulation)

Substituting:

Nadjusted =4731 + (473/1600) = 365

Thus, we will aim to recruit 365 people for this study. 

Assumptions and Considerations:

  • The expected sensitivity of the Foldscope is assumed to be 80% based on preliminary estimates.

  • The 52% prevalence is a liberal estimate that represents historically high infection rates (Ekpo, 2012) observed in Oyan Reservoir communities, but this is likely far higher than the existing situation today in Imala, while Imala Odo likely faces much higher prevalence. There is a lack of existing up-to-date data in this region, so we are using this number to reflect an approximate average for the region based on existing data.  

  • A 5% precision margin aligns with standard diagnostic accuracy study methodologies.

  • The study is primarily focused on sensitivity estimation; specificity assessment is exploratory and may be limited due to the high prevalence of infection.

Thus, we will aim to recruit 365 people to be included for this study.

Assumptions:

  • The expected sensitivity of the Foldscope is assumed to be 80% based on preliminary estimates

  • The 52% prevalence represents an approximate average for the region based on existing data

  • A 5% precision margin aligns with standard diagnostic accuracy study methodologies

  • A 10% buffer will be added to account for potential dropout rates, meaning 400 in total as a goal for recruitment, meaning 50 people per day over an 8 day period.

3.4.2 Qualitative Components

For the qualitative data collection:

  • 10-20 CHEWs/clinicians will be recruited for in-depth interviews

  • 8-12 participants for each focus group discussion (FGD)

  • A minimum of one CHEW/clinician focus group 

  • Additional key informant interviews (KIIs) with stakeholders involved in schistosomiasis control

3.5 Sampling Methods

3.5.1 Diagnostic Accuracy Component

Participants will be selected via convenience sampling. Over the course of eight days at the study sites (distributing approximately 50 participants per day for timing considerations), participants will be recruited by community mobilizers and Health In Your Hands (HIYH) team members to attend a screening clinic. The screening clinic will be set up at locations chosen by community leadership, such as local primary schools or community meeting centers.

3.5.2 Qualitative Components

  • Healthcare workers will be recruited via convenience sampling from Imala, Imala Odo, and surrounding communities

  • FGD participants will be collected via convenience sampling (8-12 participants per group)

  • Key informants will be identified during the study and invited for interviews

3.6 Data Collection Methods

3.6.1 Diagnostic Accuracy Component

  • At least 30 mL of urine will be collected from each participant

  • 10 mL will be used for the gold standard diagnostic technique (microfiltration with polycarbonate membranes followed by standard light microscopy)

  • The remaining urine sample will be used in the experimental arm using the microfluidic device and Foldscope microscope

  • CHEWs and clinicians will conduct processing and diagnosis in the experimental arm after receiving appropriate training

  • Each participant will provide a "positive" or "negative" determination based on the identification of eggs

  • Egg counts will be performed with both methods to evaluate quantitative assessment capabilities

  • Quality control will include 3 lab scientists per lab table for verification, level of agreement will be measured by recorded assessments

  • Positive cases will be treated immediately with praziquantel

3.6.2 Qualitative Components

  • CHEWs/clinicians will participate in in-depth interviews lasting 30-60 minutes after completing the diagnostic component

  • Focus group discussions will be conducted with community members and healthcare workers

  • Key informant interviews will be conducted with relevant stakeholders

  • All qualitative sessions will be recorded, transcribed, and analyzed for themes

3.7 Data Analysis

3.7.1 Diagnostic Accuracy Data

The following metrics will be calculated using a 2×2 contingency table in GraphPad Prism:

  • Sensitivity = (TP/(TP + FN)) * 100

  • Specificity = (TN/(TN + FP)) * 100

  • PPV = (TP/(TP + FP)) * 100

  • NPV = (TN/(TN + FN)) * 100

  • Accuracy = (TP + TN)/(TP + TN + FP + FN) * 100

  • Kappa statistic (κ) = (Po - Pe)/(1 - Pe)

  • McNemar's test will be applied to compare performance between methods

  • Level of agreement between trained lab scientists and CHEWs will be assessed

rism:

Gold Standard

Foldscope Positive

Foldscope Negative

Total

Positive (True Cases)

TP (True Positives)

FN (False Negatives)

      TP + FN

Negative (Non-Cases)

FP (False Positives)

TN (True Negatives)

      FP + TN

Total

TP + FP

FN + TN

N (Total Cases)

●      Kappa statistics will be used to determine the level of agreement between the Foldscope and the gold standard diagnostic approach.

●      McNemar’s test will be applied to compare the performance of Foldscope versus gold standard microscopy.

Equations: 

Sensitivity = (TP/(TP + FN)) * 100

Specificity = (TN/(TN + FP)) * 100

PPV = (TP/(TP + FP)) * 100

NPV = (TN/(TN + FN)) * 100

Accuracy = (TP + TN)/(TP + TN + FP + FN) * 100

κ = (Po - Pe)/(1 - Pe)

Calculations:

1. Sensitivity (True Positive Rate)

Sensitivity = (TP/(TP + FN)) * 100

Measures the proportion of true infections correctly identified by the Foldscope.

2. Specificity (True Negative Rate)

Specificity = (TN/(TN + FP)) * 100

Measures the proportion of uninfected individuals correctly identified as negative.

3. Positive Predictive Value (PPV)

PPV = (TP/(TP + FP)) * 100

Indicates the likelihood that a positive Foldscope result truly represents an infection.

4. Negative Predictive Value (NPV)

NPV = (TN/(TN + FN)) * 100

Indicates the likelihood that a negative Foldscope result truly represents an absence of infection.

5. Diagnostic Accuracy

Accuracy = (TP + TN)/(TP + TN + FP + FN) * 100

Represents the overall proportion of correctly classified cases.

6. Agreement (Kappa Statistic, κ)

κ = (Po - Pe)/(1 - Pe)

Where:

●      PoPo = Observed Agreement (proportion of TP and TN combined)

●      PePe = Expected Agreement due to chance

7. McNemar’s Test

●      Used to compare the Foldscope's performance against the gold standard, testing whether the proportion of false positives and false negatives differs significantly.

All calculations will be performed using GraphPad Prism's Contingency Table and Agreement Analysis tools.

3.7.2 Qualitative Data Analysis

A thematic analysis of qualitative data will be conducted to explore perceived feasibility, acceptability, and barriers to implementing Foldscope-based diagnostics in community settings. Dedoose software will be used to facilitate coding, categorization, and pattern recognition in transcribed focus group discussions (FGDs), key informant interviews (KIIs), and structured interviews with community health extension workers (CHEWs) and other stakeholders. A deductive and inductive coding approach will be applied, incorporating predefined themes (e.g., usability, training needs, perceived accuracy) while allowing for emergent themes identified during coding. Coding reliability will be enhanced through inter-rater agreement, with discrepancies resolved through discussion. Stakeholder perspectives (e.g., CHEWs vs. community members) will be compared to identify variation in diagnostic feasibility and acceptability. Sentiment analysis will be performed to assess overall attitudes toward Foldscope implementation. Findings from FGDs and KIIs will be triangulated with diagnostic accuracy results to explore how perceived usability and feasibility correlate with Foldscope performance metrics. Descriptive statistics (e.g., frequency of themes, coding matrices) will be used to quantify qualitative findings where applicable. This approach will provide a comprehensive understanding of diagnostic implementation challenges and inform future scale-up strategies for community-based schistosomiasis control.

ETHICAL CONSIDERATIONS

Ethical approval is sought from Ogun institutional and ethical review boards. Written informed consent will be secured from all participants (or guardians for minors).Community health worker participants will be informed of the aims of the study, which will entail them answering a set of questions. Written consent will be collected for anybody participating in qualitative data collection, as well. The option to not participate will be fully communicated. For patients participating, the notification will be given that we are examining their urine and that their health information will be kept fully confidential.  Written informed consent will be obtained from each respondent and participants will not be coerced in any way. They will be given the choice to participate or not in the study and the free will to withdraw at any time if they so choose with no negative consequences and appropriate clinical care maintained. No names will be written on consent forms or questionnaires by the research team, so respondents can be assured of confidentiality. Image data stored securely on encrypted, password-protected devices with no mention of names.

4.4 Benefits and Risks

Benefits:

  • Immediate diagnosis and treatment for infected participants

  • Potential development of improved diagnostic tools for the community

  • Knowledge generation to benefit schistosomiasis control programs

Risks:

  • Minimal discomfort during urine sample collection

  • Potential breach of confidentiality (mitigated by strict data protection protocols)

4.5 Compensation and Incentives

  • CHEW/clinician participants will receive appropriate compensation upon completion of both the diagnostic and qualitative components

  • Community participants will not receive direct financial compensation but will benefit from free screening and treatment if infected

Chapter 5: Result Dissemination

5.1 Notification of Results

5.1.1 Individual Results

  • Individual test results from urine samples will be communicated within hours (estimated 10-20 minutes)

  • Positive cases will be referred for standard treatment following national guidelines

  • Participants will receive appropriate counseling about their results

5.1.2 Stakeholder Notification

  • Meetings with community health workers and local health leaders

  • Written summaries in local languages and English to enhance accessibility

  • Reports to relevant health authorities and partner organizations

5.2 Anticipated Products and Impact

  • Standardized Foldscope diagnostic protocol

  • Training materials for health workers

  • Documented themes of feasibility to inform future efforts

  • Documented themes of community acceptability and barriers

  • Data for image analysis algorithms for schistosomiasis detection

5.3 Dissemination Plan

  • Application for National Geographic's level 1 grant for Freshwater Storytelling for a 2026 media project

  • Peer-reviewed journal submissions with open-access, with credit to all parties involved

  • Regional and international conference presentations

  • Reports to relevant Nigerian health authorities

5.4 Timeline

First phase (April 2025):

  • Establish communication and collaboration with national, state, and local government leadership

  • Engage community leaders, NTD coordinators, and health workers

  • Communicate goals and methods

Second phase (July 2025):

  • Train community health workers in microscopy techniques

  • Assess diagnostic accuracy vs conventional methods

  • Gather qualitative data on feasibility and potential improvements

  • Assess infection etiology education and clinical algorithms

  • Address usability, training, and logistical challenges

  • Optimize protocols for image acquisition, interpretation, and reporting

Third phase (August-December 2025):

  • Data analysis

  • Manuscript preparation

  • Dissemination activities

5.5 Data Sharing and Accessibility

  • De-identified datasets will be shared following ethical guidelines and data privacy regulations

  • Results will be published in open-access journals to ensure information can be used and scaled up by local or international efforts

6. Bibliography

Akinwale, O. P., Ajayi, M. B., Akande, D. O., Gyang, P. V., Adeleke, M. A., & Dike, A. N. (2010). Urinary schistosomiasis around Oyan Reservoir, Nigeria: twenty years after the first outbreak. Iranian Journal of Public Health, 39(1), 92-95.

Archer, J., Barksby, R., Pennance, T., et al. (2024). Analytical and clinical assessment of a novel, high-sensitivity assay for detection of Schistosoma DNA in human urine samples. Clinical Microbiology and Infection, 30(1), 107-114.

Chatterji, S., Hotez, P. J., & Engels, D. (2024). Female genital schistosomiasis: A neglected tropical gynecologic condition and HIV risk factor. The Lancet Infectious Diseases, 24(1), e12-e18.

Dawaki, S., Al-Mekhlafi, H.M., Ithoi, I., et al. (2015). The menace of schistosomiasis in Nigeria: Knowledge, attitude, and practices regarding schistosomiasis among rural communities in Kano State. PLoS ONE, 10, e0143667.

Ephraim, R. K., Dickson, E. K., Derrick, N. B., & Wiredu, E. K. (2025). Field evaluation of the Foldscope for Schistosoma haematobium diagnosis in rural Ghana: A pilot study. PLoS Neglected Tropical Diseases, 19(1), e0011567.

Ekpo, U. F., Alabi, O. M., Oluwole, A. S., & Sam-Wobo, S. O. (2012). Schistosoma haematobium infections in preschool children from two rural communities in Ijebu East, southwestern Nigeria. Journal of Helminthology, 86(3), 323-328.

Ezeh, C.O., Onyekwelu, K.C., Akinwale, O.P., Shan, L., & Wei, H. (2019). Urinary schistosomiasis in Nigeria: A 50-year review of prevalence, distribution, and disease burden. Parasite, 26, 19.

Faust, C. L., Osakunor, D. N. M., Downs, J. A., et al. (2020). Schistosomiasis control: Leave no age group behind. Trends in Parasitology, 36, 582-591.

Mtethiwa, A. H., Nkwengulila, G., Bakuza, J., et al. (2015). Extent of morbidity associated with schistosomiasis infection in Malawi: A review paper. Infectious Diseases of Poverty, 4, 25.

Sharma, S. K., Mudgal, S. K., Gaur, R., Chaturvedi, J., Rulaniya, S., & Sharma, P. (2024). Navigating sample size estimation for qualitative research. Journal of Medical Evidence, 5(2), 133-139. https://doi.org/10.4103/JME.JME_59_24

Van, G. Y., Onasanya, A., van Engelen, J., Oladepo, O., & Diehl, J. C. (2020). Improving access to diagnostics for schistosomiasis case management in Oyo State, Nigeria: Barriers and opportunities. Diagnostics, 10(5), 328.

Vasileiou, K., Barnett, J., Thorpe, S., et al. (2018). Characterising and justifying sample size sufficiency in interview-based studies: Systematic analysis of qualitative health research over a 15-year period. BMC Medical Research Methodology, 18, 148. https://doi.org/10.1186/s12874-018-0594-7

Xiao, Y., Lu, Y., Hsieh, M., Liao, J., & Wong, P. K. (2016). A microfiltration device for urogenital schistosomiasis diagnostics. PLoS ONE, 11(4), e0154640. https://doi.org/10.1371/journa...


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