Informatics Tools applicable to diverse entomological studies of mosquitoes Samson Kiware Research Scientist/Wellcome Trust Fellow Ifakara Health Institute, Tanzania

Motivation statement Standardized data schema, databases and even public data repositories exist for genetic data for malaria parasites and for their human and mosquito hosts and similar controlled and standardized systems are available for epidemiological studies of malaria-infected human beings. However, equivalent systems for studies of the mosquitoes which mediate transmission are only now emerging 2

Challenges on entomological studies 3 SOME OF CHALLENGES 2. Experiment- specific forms: error prone 3. Forms Re-design for each new Experiment 4. Variety of data formats 5. Difficulty in linking field & laboratory data 6. Difficulty in data sharing 7. Collect large volume of data 1. Experimental Designs

Solution What is needed? Improved informatics tools to provide structure to data at the point of data collection and streamline use of databases that consistently link field and laboratory data Solution Develop a generic schema to record taxonomic, abundance and phenotypic data, as well as processing associated samples Generic schema a foundation Develop data collection forms Electronic data collection forms Online Data repository Target users Lower-income tropical countries with limited access to specialized software and expert informatics support. 4

Generic schema based on procedures 5 Common Procedures (most experiments follow them) Sorting Constitution Observati on Sample processing Experime nt design Field or laboratory population Sorting BatchIndividual Pool Observatio n 1 n n 1 1 n 1 1 n n n Sample Sorting Sample Collection Experimental Design Sample Constitution Sample Observation

Main tables for the generic schema 6

Data collections forms Paper based data collection forms are produced based on the generic schema Forms in Excel are available here – Additional file 1here Examples of the forms used for adult mosquito experiments are provided in the next few slides 7

Experiment Design: Field Collection Form 8 Data on Where? When? How? Opportunity to pre-fill Project information Accountability

Sample Sorting Adult Field Collection Form 9

10 Sex and Abdominal Status Taxon descriptions

Sample Labelling: 11 Instructions are provided on 1.How to label the samples 2.Pack the samples 3.How to record label information the lab form

Sample Observation: Laboratory analysis 12 Species & Blood-meals Identification, infection status 1.Field technician record sample label info 2.Field technician mark fields (RQ) for required analysis 1.PCR 2.CSP ELISA 3.Bloodmeal ELISA 3.Lab technician provided results in grey columns (RS)

Sample Storage 13 Storage Temp, No. samples, refrigerator & rack # Record storage information for samples

Master data dictionary – A Snapshot 14 All variables are well defined – they can be in any language – attribute code for each variable is kept constant

Entomological malaria indicators As an example: these tools are able to capture the following indicators: Vector relative abundance Vector season distribution Presence of malaria vectors and species Parous rates Insecticide susceptibility Indoor/outdoor feeding behaviour Times of feeding Human biting rates Host preference Vector capacity and EIR (can be computed) 15

General Schema -> Electronic Version 16 We are currently developing and testing electronic version for the data collection forms using ODK platform Advantages Customizable Checks – entry point Labelling – barcodes GPS recording Synchronization – server Provide real time data in some cases Challenges Power/durability Resources

Ifakara Entomology Bioinformatics System (IEBS) 17 What can you do with the system? IEBS (link) Applicationlink Secure & Free Users just needs to obtain ID from us and register A database web-based application is available to process data collected on paper forms or electronic devices

Ifakara Entomology Bioinformatics System (IEBS) 18 What can you do with the system? PI can add Project & Experiments Provide Access – Project Upload Using customizable Templates Language Independent Link field and laboratory Download -.csv file Share data easily Access Data Dictionary

Why these tools? Can be used as a standardized entomological surveillance for most studies Save time required for data preparation No need to Redesign Forms No need to reformat data from multiple sources Data sharing made easier Digital object identifier (doi) provided Quality data on the ground Less data cleaning Train Field Technicians once – can work for any other experiments 19

Why these tools? Language Independent Possible to link to other databases Demographic Surveillance System – using house number Epidemiology based databases – require agreement of the key to use Help to address bigger questions Compare studies from multiples experiments, projects and study sites Support Evidence-based decisions Provide quality data to inform vector control models 20

Going forward Increase number of users Currently: 20 experiments 8 projects 8 project investigators Collaborating NMCPs Zanzibar, and Zambia 10 peer-reviewed publications Test and Implement mobile data collection Add more functionalities to IEBS as per user’s request Re-format historical data to store for different experiment & projects 21

Summary 22 Data recording Data entry Data processing Data dissemination - Smart Trap Adult or immature samplinglaboratory or field populations Generic schema Most experiments PDAsPaper forms Data collection forms Resources & Preference /Standardized data formats Database server Data Linkage, cleaning, Mean biting rate of Report generation MAP GenBank Data dissemination Report generation Data Sharing

Summary 23 Data recording Data entry Data processing Data dissemination Mean biting rate of Report generation Adult or immature samplinglaboratory or field populations - MAP GenBank PDAsPaper forms Database server Focus: Quality ground data

Acknowledgement 24 Additional files are provided with this article on the following:article Paper-Based Data Collection Forms Detailed Description of the Generic Schema and Forms Selected examples to illustrate how the forms work A lot of scientists have contributed to this work – some listed as co-authors