[OSGeo Africa] Request for HIV Prevalence for North West Province - Ngaka Modiri Molema District Municipality
Calle Hedberg
chedberg at telkomsa.net
Tue Aug 2 07:54:58 PDT 2016
Hi
What type of HIV prevalence data are you looking for?
1. The annual antenatal HIV survey has since 2006 provided prevalence data for pregnant women down to the district level.
2. Various other surveys have been done in the past – see the Human Sciences Research Council web-site for details.
3. There are various other models for HIV prevalence and incidence available – see the UNAIDS web-site (multi-country estimates) and the web-site of the Actuarian Society of South Africa (SA model).
4. I think a few more models and estimates have been published in the past, but I don’t have references.
5. I would also check through the agenda for recently concluded global AIDS conference in Durban – any new research or prevalence models would probably have been presented there.
Best regards
Calle
Health Information Systems Program – South Africa
From: Africa [mailto:africa-bounces at lists.osgeo.org] On Behalf Of Flora Makgale
Sent: 02 August 2016 12:07 PM
To: Africa local chapter discussions
Subject: [OSGeo Africa] Request for HIV Prevalence for North West Province - Ngaka Modiri Molema District Municipality
Good day Colleagues
Can someone assist with HIV Prevalence data for Ngaka Modiri Molema District Municipality in the North West Province? Either spreadsheet or dataset will be appreciated.
Regards,
Flora Makgale
Sent from my Samsung Galaxy smartphone.
-------- Original message --------
From: Calle Hedberg <chedberg at telkomsa.net>
Date: 01/08/2016 23:05 (GMT+02:00)
To: 'Africa local chapter discussions' <africa at lists.osgeo.org>
Subject: Re: [OSGeo Africa] Recent main place or sub-place spatial data for SA
Francois,
What layer to use depends on the purpose.
I’ve looked at all the three layers Helene sent me now:
- Main place layer with around 14,000 polygons, including names
- Sub-place layer with over 22,000 polygons, including names and including population count (although 1.3 mill less than the Small Area Layer)
- The Small Area Layer with over 90,000 polygons, without names but including population count (1.3 mill more than SP layer).
For the purpose of establishing a standard list of know “localities” that patients can use to describe where they live, SAL is useless – it only have numbers/codes. The SP layer is far better than the MP layer here, because the “main places” are too generic/large in many cases, especially urban areas. Take a look at this example from Tshwane – it should be obvious that the SP-names (sub-places) are far more useful as location names than the main place name (Akasia). People will know they live in Akasia, of course, but they will more typically say they live in Amandasig or Heather View or Rosslyn if asked where they live. Since the main purpose of capturing their address and “location” would be to possible send out case investigators to check for other disease cases or look for nearby ponds etc where the mosquitos breed, the more local the better.
_SP11_Pop
SP_CODE
SP_NAME
MP_CODE
MP_NAME
799037017
Amandasig
799037
Akasia
799037010
Chantelle
799037
Akasia
799037012
Clarina
799037
Akasia
799037018
Heather View
799037
Akasia
799037016
Heatherdale AH
799037
Akasia
799037014
Hesteapark
799037
Akasia
799037011
Karenpark
799037
Akasia
799037004
Klerksoord
799037
Akasia
799037019
Ninapark
799037
Akasia
799037003
Onderstepoort Nature Reserve
799037
Akasia
799037002
Rosslyn
799037
Akasia
799037001
Rosslyn Industrial
799037
Akasia
799037005
The Orchards
799037
Akasia
799037007
The Orchards Ext
799037
Akasia
799037009
The Orchards Ext 11
799037
Akasia
799037006
The Orchards Ext 21
799037
Akasia
799037008
The Orchards Ext 24
799037
Akasia
799037015
Theresapark
799037
Akasia
799037013
Winternest AH
799037
Akasia
In cases where you want e.g. population break-downs for non-standard areas – like health sub-districts in the metros, which often don’t follow ward boundaries – the SAL is clearly superior. So it’s all about purpose....
Again, my apologies if the thread is getting into too much detail – but these challenges are common when trying to use generic spatial data sets of varying granularity and with varying degree of attribute data for special purposes like tracking diseases...
Regards
Calle
From: Venter, Francois (GPHEALTH)
Sent: Monday, August 01, 2016 8:50 PM
To: Calle Hedberg (calle at hisp.org)
Subject: RE: [OSGeo Africa] Recent main place or sub-place spatial data for SA
Hi Calle,
I wanted to reply this morning just before I saw Helene’s reply to you. I will also suggest the small area layer as a working layer, seeing that it is ever smaller than the sub-place layer. However just a quick heads-up, I am not sure what the layer looks like from Helene, but if it is the same as the one I have, then you will see that there are a lot of “islands” in it which is blank. Those are excluded for the sake of reserving people’s confidentiality. You can confirm from Helene but as far as I understand, you can allocate a value of 0 to those areas, because StatsSA already assigned those values to the surrounding areas closest to those.
I hope this helps.
Regards
Francois
From: Africa [mailto:africa-bounces at lists.osgeo.org] On Behalf Of Calle Hedberg
Sent: Monday, August 01, 2016 8:16 PM
To: 'Africa local chapter discussions'
Subject: Re: [OSGeo Africa] Recent main place or sub-place spatial data for SA
UID09duf63i2bd
Hi,
Just a follow-up of my inquire about this earlier today:
1. Helene Verhoef from StatsSA provided me with the relevant layers earlier this afternoon. EXCELLENT service - my type of GIS expert :-)
2. She also told me that anybody visiting a StatsSA office can get a copy of the Small Areas data set, released in 2013, onto their laptops (my impression was that it's been distributed internally on 3 DVDs, which probably means that it is too much data for normal downloads). Furthermore, something of high relevance for e.g. the Malaria program and others working with local communities and residences/dwellings: StatsSA has coordinates for around 14 mill dwellings in the country - probably around 90%+ of the total - and successfully used some months back for the Community Survey 2016. Bona Fide users (like other government departments) can thus use the same data set as a basic framework for their work with households/dwellings.
3. Finally, Helen also told me that AfriGIS has digitized all the postal areas in the country - I will contact them about access/cost.
If all the above is known stuff, I apologise - but if not, others might find the info useful.
Regards
Calle
-----Original Message-----
From: Africa [mailto:africa-bounces at lists.osgeo.org] On Behalf Of Calle Hedberg
Sent: 01 August 2016 09:44 AM
To: 'Africa local chapter discussions'
Subject: [OSGeo Africa] Recent main place or sub-place spatial data for SA
Hi,
Disease surveillance, and in particular the Malaria program, has for many years used a set of "localities" (villages, suburbs, etc) to determine the origin or residence of e.g. malaria cases.
That level of detail/granularity is similar to the so called "sub-place" layer released by StatsSA in 2003 - containing around 21,500 local areas (although a number of them are sparsely populated areas with no name).
We are now revamping and consolidating the system for disease surveillance, which require a spatial data set with similar granularity but preferably newer than 2001/2003. I already have the ward layers for 2011 and 2016 - using wards is too coarse for our purposes, and most patients would not easily use wards as a reference to where they live.
1.
StatsSA said 2-3 years ago that they had updated the so called "main place" layer, but I cannot find any download links on their website. Anybody knows where to get that layer?
2.
There was no mention in that news item of the "sub-place" layer - anybody knows if a new (well, probably based on Census 2011) sub-place layer is available anywhere?
3.
Another option would be to build a clustered Enumeration Area layer - is the Census 2011 EA layer available from anywhere?
4.
Final question: the list of postal codes from SAPO is at the same level of granularity as the sub-place layer. I know SAPO never developed or at least released spatial data for their postal areas - have anybody else attempted to do that work for them?
Best regards
Calle Hedberg
Cape Town
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