The following resources were freely available on the web at the time of posting. I’m putting these here mostly to reduce the burden on my browser’s bookmarks folders…
Bones and Behavior Working Group: Has the “Integrative measurement protocol for morphological and behavioral research in human and non-human primates” available for free download. (Also has protocols for biomarkers from dried blood spots, urine, and saliva.)
EpiSurveyor: Allows data collection from mobile phones. DataDyne offers a free version for small scale projects. (No mobile phone signal at my study communities, but some day….)
Gapminder.org: Awesome content. Data sets you can play with.
Global Health Data Exchange (GHDx): Catalog of the world’s health and demographic data sets compiled by the Institute for Health Metrics and Evaluation.
Google’s Public Data Explorer: Great datasets, including Outbreaks 1996-2009 and Google Flu Trends Estimates.
PAHO/OPS: Great datasets for the Americas. (In the past I have sometimes found better access to data in the Spanish version of the website – the current site looks newer and better updated.)
World Bank: Has health, nutrition and population database, Millenium Development Goals database, and other helpful databases (i.e. poverty, development index, education, etc.).
Paraguay’s Direccion General de Estadistica, Encuestas, y Censo: Has some great publications, including maps, the Censo Indigena, and MECOVI projects. Sometimes links are broken, but if you come back later you can get access to the page or file you’re looking for…
Global Health References
Hesperian Foundation: Offers free downloads of their titles, which include “Where there is no doctor/Donde no hay doctor.” Great companions for the field and training community health workers. You can also buy print versions.
Healthy Villages: A guide for communities and community health workers: From the WHO library. Also fantastic.
Global Health Library: WHO project to consolidate the major sources of global health information.
GPS Data Team: Has a free online POI editor that lets you convert between different GPS file formats.
Google Maps: I find it easiest to import my GPS data here to make my own maps using My Maps.
Google Earth: Also great for map-making (but don’t have room for it on my netbook).
Centre for Indigenous Peoples’ Nutrition and Environment at McGill University: Has a protocol for Documenting Traditional Food Systems of Indigenous Peoples and links to Food and Nutrition Tables for several indigenous groups around the world. They also have guidelines for participatory health research with indigenous groups on their site, which are useful for the IRB process.
Paraguay’s Food Composition Tables: Limited foods.
Argentina’s Food Composition Tables: Argentina and Paraguay share a lot of the same foods. This table covers some of what’s missing from Paraguay’s tables.
FAO’s Latin American Food Composition Table: Aggregates food composition data from several countries.
UCSC genome brower: Lots of genomes (neanderthal!), and microbes from NCBI GenBank/RefSeq.
Ensembl.org: Lots of genomes, but few pathogens. Some genomes not available in UCSC genome browser.
Broad Institute: Have a big Mycobacterium tuberculosis sequencing project going on. Other pathogens too. You can download the sequences from their website.
Pasteur Institute: List of Mycobacterial genome-sequencing projects.
Genomes OnLine Database (GOLD): Lots of bacterial genomes.
MEGA: Molecular Evolutionary Genetic Analysis software
Oligocalc: Oligonucleotide properties calculator
Mendeley: Free reference management software that can read the bibliographic data off of the pdfs you import (i.e. no filling out entries line by line!!). Tons of other awesome features.
The Decision Tree for Statistics: If you need some help deciding what statistical test to use.
EpiInfo: From the CDC, for epidemiological analyses.
OpenEpi: Calculates epidemiological statistics online, or you can download the software and use it offline.
R: I don’t know how to use this statistics program yet, but I will probably have to learn since access to SPSS/PAWS over the university’s network can be temperamental over long distances. Non-computer programming types beware. These look like good places to start learning: (1) “Introduction to Probability and Statistics Using R” by G. Jay Kerns, (2) “An Introduction to R” by W.N. Venables, D.M. Smith and the R Development Core team, and (3) “Biological Data Analysis Using R” by Rodney J. Dyer.
Express Scribe: Digital transcription playback software.