Total sample use of reproductive health services.

Descriptive analyses of contraceptive, antenatal and postnatal care use by Bangladeshi married adolescents and young women. The percentage of women using at least one service was also calculated.</p

Bivariate analysis of the relationships between sample characteristics and exposures, to use of reproductive health services.

Bivariate analysis of the relationships between sample characteristics and exposures, to use of reproductive health services.</p

Demographic characteristics and rates of exposure to media, internet and migration of married women aged 15–24 years in Bangladesh.

Demographic characteristics and rates of exposure to media, internet and migration of married women aged 15–24 years in Bangladesh.</p

Logistic regression analysis between exposure variable and reproductive health service use, stratified by area, for married women aged 15–24 years living in rural (n = 1425) and urban (n = 240) areas in Bangladesh.

Logistic regression analysis between exposure variable and reproductive health service use, stratified by area, for married women aged 15–24 years living in rural (n = 1425) and urban (n = 240) areas in Bangladesh.</p

Logistic regression analysis between exposure variables and reproductive health services for married women aged 15–24 years in Bangladesh.

Logistic regression analysis between exposure variables and reproductive health services for married women aged 15–24 years in Bangladesh.</p

Additional file 3: Table S5. of Seeking consent for research with indigenous communities: a systematic review

International guidelines for seeking consent for research with Indigenous populations. (XLSM 39 kb

A comparison of ICU (bed occupancy) produced by different social distancing (SD) profiles.

The plot contrasts (i) dynamic SD levels, adjusted for phase 6 by scaling with 0.77 to capture ICU cases due to COVID-19 (solid black), (ii) non-adjusted dynamic SD levels to represent all ICU cases (dotted black), and (iii) static SD levels (SD1 = 0.2, shown in red; SD2 = 0.7, shown in green). The simulated ICUs are offset by 7 days. Coloured shaded areas around the solid line show standard deviation. Changes in dynamic SD-adoption are marked by vertical dashed black lines. Traces corresponding to each simulated scenario are computed as the average over 20 runs. SD adoption is combined with other interventions (i.e., school closures, case isolation, and home quarantine). The actual time series (black crosses), shown from 26th November 2021, aligns with the start of the Omicron outbreak in Australia. Shaded areas in grey and blue show the emergence of variants of concern and sub-lineages over time, identified in weekly genomic surveillance reports (NSW Health).</p

Incidence and disease burden of COVID-19 in Australia between 26th November 2021 and 13th June 2022.

Shaded areas in grey and blue show the emergence of variants of concern and sub-lineages over time, identified in weekly genomic surveillance reports (NSW Health). Top (a): Black (y-axis, left): a 7-day moving average of reported COVID-19 daily incidence. Orange (y-axis, right): COVID-19 related deaths. Middle (b): Black (y-axis, left): COVID-19 hospitalisations (bed occupancy). Orange (y-axis, right): COVID-19 ICU cases (bed occupancy). Bottom (c): Black (y-axis, left): COVID-19 ICU cases (bed occupancy); Orange (y-axis, right): Daily COVID-19 related deaths (solid), daily COVID-19 deaths (dashed). The data for COVID-19 cases, hospitalisation and ICU occupancy, and mortality are published by the Australian government.</p

Survival estimates by age.

<p>Kaplan-Meier survival estimates by age group for those aged 25 and older who initiated treatment in Zomba District between 1 July 2005 and 30 June 2010. Blue is 25–49 (N = 7297); Red is 50–59 (N = 839); Green is 60+ (N = 276).</p