Formula for the calculation of ART output.

<p>Formula for the calculation of ART output.</p

Number of patients in thousands on ART and CD4 monitoring by end of fiscal year in Tanzania; staff requirements and budget for each fiscal year according to the CTP.

*<p>The external input into salary costs.</p

ART output.

<p>The number of patients on ART in Tanzania according to end of year numbers of WHO's “3 by 5” initiative and mid-year numbers of CTP and five scenarios. Finally the reported number of patients initiated on ART as the thick grey line running up till the end of February 2008.</p

AIDS deaths.

<p>Estimated number of AIDS deaths without ART from 1999 to 2009 and with ART according to the five scenarios and to the CTP from 2004 to 2009.</p

Actual and authorized number of clinicians at different types of health facilities in Tanzania in the fiscal year 2001/2.

*<p>Ministry of Health/Civil Service Department Staffing levels for health facilities/institutions. Dar es Salaam 1999.</p>**<p>Ministry of Health, Census of Human Resources for Health for 2001/2.</p>***<p>Includes one military hospital.</p

Input estimates for productivity and losses and outcomes obtained mid-year 2009 for the five scenarios and the CTP based on the formula.

*<p>includes age-specific mortality of 1%+losses to follow-up and non-adherence+1^st year AIDS mortality.</p>**<p>includes age-specific mortality of 1%+losses to follow-up and non-adherence.</p>***<p>total number of AIDS deaths minus the sum of the number of new patients per year 2004–2009.</p

Surveillance of HIV and syphilis infections among antenatal clinic attendees in Tanzania-2003/2004-2

<p><b>Copyright information:</b></p><p>Taken from "Surveillance of HIV and syphilis infections among antenatal clinic attendees in Tanzania-2003/2004"</p><p>BMC Public Health 2006;6():91-91.</p><p>Published online 10 Apr 2006</p><p>PMCID:PMC1459129.</p><p>Copyright © 2006 Swai et al; licensee BioMed Central Ltd.</p

Additional file 1: Figure S1. of Profile, knowledge, and work patterns of a cadre of maternal, newborn, and child health CHWs focusing on preventive and promotive services in Morogoro Region, Tanzania

Overview of Integrated Program MNCH CHW rollout per district. Figure S2. Mean composite scores for CHW knowledge and reported service provision on maternal and child health care across the continuum of care and for specific services. Figure S3. Observed use of job aids during pregnancy home visits (n = 37). Table S1. Ordered logistic regression models for composite scores for overall CHW knowledge and specific sub-domains of pregnancy, postpartum, newborn care, and child health controlling for gender, date of training, education, age, and assets. Table S2. Ordered logistic regression models for composite scores for family planning, infection/injury prevention, malaria, HIV transmission, and nutrition controlling for gender, date of training, education, age, and assets

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions