3.2.2.2 Prepare source file for statistics

Next you need to prepare your statistics source file. This is a csv file for the statistical parameters that are used to calculate performance metrics and completeness rates. You can import and create csv files in Excel or Google Drive. Using our statistics.csv as an example, download and create a new csv file with the statistical information for your country.\

adminPcode	name	male_population_2008	female_population_2008	population_2008	crude_birth_rate_2008	male_population_2009	female_population_2009	population_2009	crude_birth_rate_2009	male_population_2010	female_population_2010	population_2010	crude_birth_rate_2010	male_population_2010	female_population_2010	population_2010	crude_birth_rate_2010	male_population_2012	female_population_2012	population_2012	crude_birth_rate_2012	male_population_2013	female_population_2013	population_2013	crude_birth_rate_2013	male_population_2014	female_population_2014	population_2014	crude_birth_rate_2014	male_population_2015	female_population_2015	population_2015	crude_birth_rate_2015	male_population_2016	female_population_2016	population_2016	crude_birth_rate_2016	male_population_2017	female_population_2017	population_2017	crude_birth_rate_2017	male_population_2018	female_population_2018	population_2018	crude_birth_rate_2018	male_population_2019	female_population_2019	population_2019	crude_birth_rate_2019	male_population_2020	female_population_2020	population_2020	crude_birth_rate_2020	male_population_2021	female_population_2021	population_2021	crude_birth_rate_2021	male_population_2022	female_population_2022	population_2022	crude_birth_rate_2022
AWn3s2RqgAN	Central	177555	170774	348377	19.4	181676	175555	357291	19.6	188087	181116	369261	18.8	189251	182171	371480	17.6	191308	183928	375281	16.6	197533	190359	387958	17.9	143825	141233	285059	17.6	145664	142059	287723	19.3	149012	146810	295822	17.7	151786	149045	300831	16.6	152859	150197	303057	18.2	155068	139186	294255	16.9	152874	144456	297331	17.3	163391	148928	312320	17.6	387162	299071	686233	6.99
KozcEjeTyuD	Sulaka	201028	186018	387046	19	201079	187184	388263	21.1	205044	189817	394861	17.6	207035	192464	399499	18.6	213349	199019	412368	20.3	213774	197747	411521	19	187272	180532	367806	18	175569	173179	348750	18.7	305507	306748	612257	19.7	309110	309404	618515	21.6	292729	289899	582630	20.1	303743	320864	624608	20	347497	306895	654393	18.1	365242	330116	695358	16.7	356247	297534	653781	17.9
B1u1bVtIA92	Pualula	245834	229646	475481	21	245920	228128	474048	22.7	252761	234940	487701	19	253865	236282	490147	19.5	260700	241754	502454	19.2	264423	245103	509534	18	267310	259051	526363	18.8	261220	257310	518530	19.4	280519	275429	555948	18.8	284831	280377	565210	20.1	278730	273515	552247	17.6	285236	269631	554868	17.2	300896	285807	586704	15.1	269712	303358	573070	15.3	260244	308373	568617	16.1

Each row will represent a unique set of statistics for an administrative division in your country.

Notice that the adminPcode and name columns are identical to applicable levels created in the csv file in the previous step.

The next 4 columns are repeated for however many years you are able to source data from your statistical department. Each year MUST contain a minimum of 4 columns:

• male_population_<year>

• female_population_<year>

• population_<year>

• crude_birth_rate_<year>

Be careful when adding extra years to not have any spaces in your headers between the name of the header and the year key.

You can remove year blocks of 4 columns if you do not have this data, but make sure the available years that you do have run consecutively without any time gaps.

You can add statistical data to a location every year using the FHIR Location API.

Note: crude death rate is applied globally in the 3.2.8 Set up Application Settings step later in this documentation.

Note: At this stage, there is not too much point in you entering data more than 5 years back in time as OpenCRVS can only calculate completeness rates based on the registration information it has available. In future versions, we plan to introduce legacy data import to include historical registrations. At that point, a history of population data becomes really powerful.

Do not change or re-format the header row as the seeding process requires these names to be precise in order to parse the csv. Do not use commas in any cell and do not have any empty rows.