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Description The General Medical History (GMH) toolkit can be used to collect essential phenotypes associated with GMH research, including: medical history related to allergies, pregnancy(ies), surgeries, vision and hearing disorders, mental disorders, respiratory system disorders, nervous system disorders, musculoskeletal system disorders, endocrine system disorders, digestive system disorders, cardiovascular system disorders, urogenital system disorders, circulatory system disorders, integumentary system disorders, sexually transmitted diseases, and developmental disorders. Administration The phenotype protocols contained in the toolkit are Interviewer/Self-administered questionnaires. The toolkit is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: Protocol - Immunizations (www.phenxtoolkit.org/protocols/view/161001)

Additional file 2. Supplementary Table 2: List of the documents in the tiered e-consent framework Github repository.

Description The Lifestyle Factors toolkit can be used to collect essential phenotypes associated with Lifestyle Factors in biomedical research, including: Physical Activity, Diet, Sleep Habits and more. Administration The phenotype protocols contained in the toolkit are Interviewer/Self-administered questionnaires, applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: WHO Global Physical Activity Questionnaire (www.who.int/ncds/surveillance/steps/GPAQ/en/) Protocol - Dietary Intake (www.phenxtoolkit.org/protocols/view/231201) Protocol - Dietary Supplements Use (www.phenxtoolkit.org/protocols/view/50501) Protocol - Caffeine Intake (www.phenxtoolkit.org/protocols/view/50301) Pittsburgh Sleep Quality Index (www.sleep.pitt.edu/instruments/)

Additional file 4. Supplementary data file 2: Example of consent dashboard.

Description The Cardiovascular Disease (CVD) toolkit can be used to collect essential phenotypes associated with CVD related research, including; Anthropometrics, CVD History (Angina, Heart Attack, Congestive Heart Failure, Thyroid Disease) and more. Administration The phenotype protocols contained in the toolkit range from Interviewer/Self-administered questionnaires to clinically-administered and bioassay/lab-based assessments. The module is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: Protocol - Angina (www.phenxtoolkit.org/protocols/view/40601) Protocol - Myocardial Infarction (www.phenxtoolkit.org/protocols/view/40801) AWI-Gen Collaborative Centre - Cardiometabolic Disease Research Instruments Stroke Investigative Research & Educational Network (SIREN) Instruments Owolabi MO, Akpa OM, Made F, Adebamowo SN, Ojo A, Adu D, Motala AA, Mayosi BM, Ovbiagele B, Adebamowo C, Tayo B, Rotimi C, Akinyemi R, Gebregziabher M, Sarfo F, Wahab KW, Parekh RS, Engel ME, Chisala C, Peprah E, Mensah G, Wiley K, Troyer J, Ramsay M; as members of the CVD Working Group of the H3Africa Consortium. Data Resource Profile: Cardiovascular H3Africa Innovation Resource (CHAIR). Int J Epidemiol. 2019 Apr 1;48(2):366-367g. doi: 10.1093/ije/dyy261. PMID: 30535409; PMCID: PMC6469307.

Description The Infectious Disease toolkit can be used to collect essential phenotypes associated with Infectious Disease related research, including information related to Malaria, Trypanosomiasis / Sleeping Sickness, Tuberculosis (TB) and HIV. Administration The phenotype protocols contained in the toolkit range from Interviewer/Self-administered questionnaires to clinically-administered and bioassay/lab-based assessments. The toolkit is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: H3Africa Case Report Form Instruments Sickle In Africa Core Data Elements (www.sickleinafrica.org/SIA_data_elements) Allie, T., Jackson, A., Ambler, J., Johnston, K., Du Bruyn, E., Schultz, C., Boloko, L., Wasserman, S., Davis, A., Meintjes, G., Wilkinson, R. J., & Tiffin, N. (2021). TBDBT: A TB DataBase Template for collection of harmonized TB clinical research data in REDCap, facilitating data standardisation for inter-study comparison and meta-analyses. PloS one, 16(3), e0249165. https://doi.org/10.1371/journal.pone.0249165 Protocol - Sexual Risk Behavior - Male (www.phenxtoolkit.org/protocols/view/101701) Protocol - Sexual Risk Behavior - Female (www.phenxtoolkit.org/protocols/view/101702) Enhanced COVID-19 Notifiable Medical Conditions (NMC) Notification Form (SA) WHO Global COVID-19 Clinical Platform: Rapid core case report form Protocol - Complete Blood Count (CBC) (www.phenxtoolkit.org/protocols/view/220501) Protocol - Liver Function - Assay (www.phenxtoolkit.org/protocols/view/190801) Protocol - Sexual Risk Behavior - Male (www.phenxtoolkit.org/protocols/view/101701) Protocol - Sexual Risk Behavior - Female (www.phenxtoolkit.org/protocols/view/101702) HIV Cohorts Data Exchange Protocol (https://hicdep.org/)

Additional file 6. Supplementary data file 4: Example of study population data summarised for each type of consent.

Additional file 1. Participant information and informed consent checklist for new research study.

Description The H3Africa core phenotypes can be used to collect essential phenotypes related to African health and biomedical research. These phenotypes were prioritised based on the overlap in phenotype data collection across multiple research projects being conducted across the African continent, in various disease fields. Phenotypes include information related to a participant’s demographics, anthropometrics, tobacco and alcohol use, and disease history. Administration The phenotype protocols contained in the toolkit range from Interviewer/Self-administered questionnaires to clinically-administered and bioassay/lab-based assessments. The toolkit is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: AWI-Gen Collaborative Centre - Cardiometabolic Disease Research Protocols Protocol - Blood Pressure (www.phenxtoolkit.org/protocols/view/40301) Protocol - Cigarette Smoking Status (www.phenxtoolkit.org/protocols/view/30604) Protocol - Tobacco - 30-Day Quantity and Frequency (www.phenxtoolkit.org/protocols/view/30804) Protocol - Alcohol - Lifetime Use (www.phenxtoolkit.org/protocols/view/30101) Protocol - Substances - 30-Day Frequency (www.phenxtoolkit.org/protocols/view/31302) Protocol - Medication Inventory (www.phenxtoolkit.org/protocols/view/140301) Protocol - Personal History of Type I and Type II Diabetes (www.phenxtoolkit.org/protocols/view/140501) Protocol - Personal History of Kidney Failure (www.phenxtoolkit.org/protocols/view/140601) Protocol - Arrhythmia (www.phenxtoolkit.org/protocols/view/41101) Protocol - Rheumatic Fever/Rheumatic Heart Disease (www.phenxtoolkit.org/protocols/view/41401) Protocol - History of Stroke (www.phenxtoolkit.org/protocols/view/130301)

Description The Kidney Disease toolkit can be used to collect essential phenotypes associated with Kidney Disease-related research including personal History of Kidney Failure, Kidney Function Assay and Blood Cell Count. Administration The phenotype protocols contained in the toolkit range from Interviewer/Self-administered questionnaires to bioassay/lab-based assessments. The toolkit is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: Kumuthini J, van Woerden C, Mallett A, et al. Proposed minimum information guideline for kidney disease—research and clinical data reporting: a cross-sectional study, BMJ Open 2019;9:e029539. DOI: 10.1136/bmjopen-2019-029539 Protocol - Personal History of Kidney Failure (www.phenxtoolkit.org/protocols/view/140601) Protocol - Complete Blood Count (CBC) (www.phenxtoolkit.org/protocols/view/220501) Sickle In Africa Core Data Elements (www.sickleinafrica.org/SIA_data_elements)

Description The Environmental Exposures toolkit can be used to collect information pertaining to: socio-economic status, occupational history, water resources and more. Administration The phenotype protocols contained in the toolkit range from Interviewer/Self-administered questionnaires to bioassay/lab-based assessments. The toolkit is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: H3Africa Case Report Form Instruments Protocol - Occupation/Occupational History (www.phenxtoolkit.org/protocols/view/60501) Protocol - Air Contaminants in the Home Environment (www.phenxtoolkit.org/protocols/view/61101) Protocol - Personal Care Products (www.phenxtoolkit.org/protocols/view/61501) Protocol - Home and Workplace Exposures to Floor and Wall Materials (www.phenxtoolkit.org/protocols/view/61401) WHO Core questions on drinking water and sanitation for household surveys (www.who.int/water_sanitation_health/monitoring/household_surveys/en/)

Additional file 5. Supplementary data file 3: Consent Withdrawal Dashboard.

Description The Rare & Developmental (R&D) Disorder toolkit can be used to collect essential phenotypes associated with R&D related research, including: Birth History, Neurodevelopmental History, Epilepsy and System Anomalies. Administration The phenotype protocols contained in the toolkit range from Interviewer/Self-administered questionnaires and clinically-administered assessments. The toolkit is applicable to human participants of all life stages, though some phenotype protocols are age-specific. For more information on administration of the toolkit, see the toolkit guideline. Resources The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: H3Africa DDD-Africa Case Report Forms H3Africa Rare Diseases WG Case Report Forms Protocol - Epilepsy Screener - Adult (www.phenxtoolkit.org/protocols/view/130401) Protocol - Epilepsy Screener - Child/Proxy (www.phenxtoolkit.org/protocols/view/130402)

Additional file 3. Supplementary Table 1: Additional REDCap survey customisations that were used in the tiered econsent documents.

Description The Stroke toolkit can be used to collect essential phenotypes associated with Stroke-related research, including: Stroke Characterisation; Stroke Verification; Primary Prevention and Secondary Prevention. Administration The phenotype protocols contained in the toolkit range from Interviewer/Self-administered questionnaires to clinically-administered assessments. The toolkit is specificaly applicable to adults (aged 18 and older). For more information on administration of the toolkit, see the toolkit guideline. References The toolkit consists of both existing and novel data collection standards, and was based on several existing resources. These resources are listed below: H3Africa SIREN Case Report Forms (CRFs)

Background Risk factors for coronavirus disease 2019 (COVID-19) death in sub-Saharan Africa and the effects of human immunodeficiency virus (HIV) and tuberculosis on COVID-19 outcomes are unknown. Methods We conducted a population cohort study using linked data from adults attending public-sector health facilities in the Western Cape, South Africa. We used Cox proportional hazards models, adjusted for age, sex, location, and comorbidities, to examine the associations between HIV, tuberculosis, and COVID-19 death from 1 March to 9 June 2020 among (1) public-sector “active patients” (≥1 visit in the 3 years before March 2020); (2) laboratory-diagnosed COVID-19 cases; and (3) hospitalized COVID-19 cases. We calculated the standardized mortality ratio (SMR) for COVID-19, comparing adults living with and without HIV using modeled population estimates. Results Among 3 460 932 patients (16% living with HIV), 22 308 were diagnosed with COVID-19, of whom 625 died. COVID-19 death was associated with male sex, increasing age, diabetes, hypertension, and chronic kidney disease. HIV was associated with COVID-19 mortality (adjusted hazard ratio [aHR], 2.14; 95% confidence interval [CI], 1.70–2.70), with similar risks across strata of viral loads and immunosuppression. Current and previous diagnoses of tuberculosis were associated with COVID-19 death (aHR, 2.70 [95% CI, 1.81–4.04] and 1.51 [95% CI, 1.18–1.93], respectively). The SMR for COVID-19 death associated with HIV was 2.39 (95% CI, 1.96–2.86); population attributable fraction 8.5% (95% CI, 6.1–11.1). Conclusions While our findings may overestimate HIV- and tuberculosis-associated COVID-19 mortality risks due to residual confounding, both living with HIV and having current tuberculosis were independently associated with increased COVID-19 mortality. The associations between age, sex, and other comorbidities and COVID-19 mortality were similar to those in other settings.