docs: network-hhmodel example: Separate contact from disease progression by swo · Pull Request #847 · CDCgov/ixa

swo · 2026-04-15T23:11:34Z

seir.rs looks for the infected people, then asks network.rs who they contact via get_contacts(). This is a nicer separation of concerns.
Make the period of the periodic plan explicit, so that get_contacts() needs a duration argument, that says what contacts will happen over what time period.
It's still clunky/non-DRY that there's no loop over edge types.

I'm having some trouble with getting the cargo +nightly fmt check to stabilize

RobertJacobsonCDC · 2026-04-20T14:57:38Z

Awesome! I think we've all felt the need for someone with modeling expertise to take a close look at our examples for quite some time now, so it's great that you're doing this. If you want to look over any other of the examples—or even add new ones that you think are conspicuously missing—definitely feel free to! But obviously don't feel obligated.

I'll look into the failing lints and get back to you. Sometimes they feel like a moving target...

RobertJacobsonCDC · 2026-04-20T15:34:22Z

I think it's not failing because of the lints. I think it's failing because the example never terminates: Cancelled after 365m.

github-actions · 2026-04-20T16:48:36Z

Benchmark Results

Hyperfine

Command	Mean [ms]	Min [ms]	Max [ms]	Relative
`large_sir::baseline`	2.9 ± 0.1	2.8	3.1	1.00
`large_sir::entities`	11.9 ± 0.2	11.5	12.5	4.13 ± 0.10

Criterion

Regressions (slower)

Group	Bench	Param	Change	CI Lower	CI Upper
indexing	`query_people_count_indexed_multi-property_entities`		29.641%	29.435%	29.808%
indexing	`query_people_single_indexed_property_entities`		18.436%	15.261%	21.345%
counts	`concrete_plus_derived_unindexed_entities`		14.357%	13.765%	14.947%
large_dataset	`bench_match_entity`		11.641%	11.337%	12.066%
large_dataset	`bench_query_population_derived_property_entities`		11.191%	9.808%	12.447%
sampling	`count_and_sampling_single_unindexed_concrete_plus_derived_entiti`		8.094%	7.948%	8.212%
large_dataset	`bench_query_population_multi_unindexed_entities`		6.421%	4.541%	8.391%
sample_entity	`sample_entity_whole_population`	100000	4.061%	3.704%	4.361%
indexing	`query_people_indexed_multi-property_entities`		3.430%	3.091%	3.794%
sampling	`sampling_single_l_reservoir_entities`		2.730%	2.356%	3.050%
sampling	`count_and_sampling_single_known_length_entities`		1.956%	1.279%	2.626%
counts	`multi_property_unindexed_entities`		1.493%	1.073%	1.914%

Improvements (faster)

Group	Bench	Param	Change	CI Lower	CI Upper
sample_entity	`sample_entity_single_property_unindexed`	1000	-20.698%	-21.835%	-19.262%
large_dataset	`bench_filter_unindexed_entity`		-16.667%	-18.878%	-14.351%
indexing	`query_people_count_single_indexed_property_entities`		-12.648%	-12.976%	-12.218%
indexing	`with_query_results_single_indexed_property_entities`		-9.443%	-10.612%	-8.151%
sample_entity	`sample_entity_multi_property_indexed`	1000	-7.862%	-8.471%	-7.233%
sample_entity	`sample_entity_multi_property_indexed`	100000	-7.158%	-7.520%	-6.698%
sample_entity	`sample_entity_multi_property_indexed`	10000	-5.657%	-6.740%	-4.117%
examples	`example-basic-infection`		-5.379%	-5.816%	-5.010%
sample_entity	`sample_entity_single_property_indexed`	10000	-5.140%	-7.038%	-3.608%
sample_entity	`sample_entity_single_property_indexed`	1000	-4.447%	-5.984%	-3.025%
counts	`single_property_unindexed_entities`		-4.299%	-5.064%	-3.350%
indexing	`query_people_multiple_individually_indexed_properties_entities`		-4.054%	-4.234%	-3.880%
sampling	`sampling_single_unindexed_concrete_plus_derived_entities`		-3.888%	-6.678%	-1.478%
sample_entity	`sample_entity_single_property_indexed`	100000	-3.103%	-3.571%	-2.627%
sample_entity	`sample_entity_single_property_unindexed`	10000	-1.784%	-2.339%	-1.203%
algorithm_benches	`algorithm_sampling_multiple_known_length`		-1.758%	-2.268%	-1.218%

Unchanged / inconclusive (CI crosses 0%)

Group	Bench	Param	Change	CI Lower	CI Upper
large_dataset	`bench_query_population_indexed_property_entities`		-1.589%	-3.674%	0.101%
algorithm_benches	`algorithm_sampling_multiple_l_reservoir`		-1.053%	-1.532%	-0.675%
counts	`single_property_indexed_entities`		-0.988%	-1.670%	-0.340%
sampling	`sampling_multiple_l_reservoir_entities`		-0.937%	-1.187%	-0.680%
large_dataset	`bench_filter_indexed_entity`		0.936%	-6.252%	9.145%
counts	`index_after_adding_entities`		-0.891%	-1.529%	-0.285%
large_dataset	`bench_query_population_multi_indexed_entities`		-0.817%	-1.115%	-0.486%
sampling	`sampling_multiple_known_length_entities`		0.550%	-0.055%	1.204%
algorithm_benches	`algorithm_sampling_single_known_length`		-0.548%	-1.010%	-0.197%
sampling	`sampling_single_unindexed_entities`		-0.533%	-0.732%	-0.412%
indexing	`with_query_results_indexed_multi-property_entities`		-0.516%	-1.347%	0.243%
sample_entity	`sample_entity_single_property_unindexed`	100000	0.472%	0.097%	0.847%
examples	`example-births-deaths`		-0.466%	-2.155%	1.368%
algorithm_benches	`algorithm_sampling_single_l_reservoir`		-0.416%	-0.779%	-0.102%
sampling	`sampling_single_known_length_entities`		0.326%	-0.155%	0.838%
sampling	`sampling_multiple_unindexed_entities`		0.319%	0.211%	0.430%
counts	`multi_property_indexed_entities`		0.253%	-0.566%	1.125%
algorithm_benches	`algorithm_sampling_single_rand_reservoir`		0.245%	-0.086%	0.516%
counts	`reindex_after_adding_more_entities`		-0.121%	-0.229%	-0.019%
indexing	`query_people_count_multiple_individually_indexed_properties_enti`		0.114%	0.027%	0.196%
indexing	`with_query_results_multiple_individually_indexed_properties_enti`		-0.085%	-0.513%	0.249%
sample_entity	`sample_entity_whole_population`	1000	-0.067%	-0.999%	0.681%
large_dataset	`bench_query_population_property_entities`		0.047%	-0.324%	0.551%
sample_entity	`sample_entity_whole_population`	10000	0.015%	-0.634%	0.447%

github-actions · 2026-04-20T16:50:50Z

Benchmark Results

Hyperfine

Command	Mean [ms]	Min [ms]	Max [ms]	Relative
`large_sir::baseline`	3.1 ± 0.0	3.0	3.2	1.00
`large_sir::entities`	11.9 ± 0.3	11.5	13.1	3.88 ± 0.10

Criterion

Regressions (slower)

Group	Bench	Param	Change	CI Lower	CI Upper
sample_entity	`sample_entity_multi_property_indexed`	10000	8.894%	8.411%	9.410%
sample_entity	`sample_entity_multi_property_indexed`	1000	8.217%	7.688%	8.677%
sample_entity	`sample_entity_multi_property_indexed`	100000	7.748%	6.891%	8.350%
sample_entity	`sample_entity_single_property_indexed`	1000	7.450%	6.847%	8.050%
sample_entity	`sample_entity_single_property_indexed`	100000	5.784%	5.103%	6.507%
sample_entity	`sample_entity_single_property_indexed`	10000	4.573%	3.872%	5.116%
sampling	`sampling_single_l_reservoir_entities`		3.217%	2.779%	3.560%
sample_entity	`sample_entity_single_property_unindexed`	10000	2.554%	1.879%	3.250%
examples	`example-births-deaths`		1.900%	1.619%	2.214%
sample_entity	`sample_entity_single_property_unindexed`	1000	1.420%	1.098%	1.870%

Improvements (faster)

Group	Bench	Param	Change	CI Lower	CI Upper
sample_entity	`sample_entity_single_property_unindexed`	100000	-24.033%	-25.364%	-22.516%
large_dataset	`bench_filter_unindexed_entity`		-20.601%	-23.138%	-18.027%
indexing	`with_query_results_single_indexed_property_entities`		-13.641%	-14.511%	-13.008%
indexing	`query_people_count_single_indexed_property_entities`		-12.532%	-12.706%	-12.330%
indexing	`query_people_indexed_multi-property_entities`		-7.333%	-7.881%	-6.674%
indexing	`query_people_single_indexed_property_entities`		-6.428%	-8.325%	-4.579%
large_dataset	`bench_match_entity`		-5.483%	-7.845%	-2.507%
indexing	`query_people_multiple_individually_indexed_properties_entities`		-4.509%	-4.824%	-4.204%
counts	`reindex_after_adding_more_entities`		-4.038%	-4.182%	-3.900%
large_dataset	`bench_query_population_multi_unindexed_entities`		-3.140%	-3.997%	-2.628%
indexing	`query_people_count_multiple_individually_indexed_properties_enti`		-2.786%	-3.179%	-2.378%
sampling	`sampling_single_unindexed_entities`		-2.242%	-2.633%	-1.869%
large_dataset	`bench_query_population_derived_property_entities`		-1.956%	-2.593%	-1.286%
sample_entity	`sample_entity_whole_population`	1000	-1.858%	-2.210%	-1.514%
counts	`single_property_indexed_entities`		-1.770%	-2.346%	-1.182%
counts	`index_after_adding_entities`		-1.730%	-2.105%	-1.412%
sampling	`sampling_multiple_unindexed_entities`		-1.252%	-1.330%	-1.152%

Unchanged / inconclusive (CI crosses 0%)

Group	Bench	Param	Change	CI Lower	CI Upper
sample_entity	`sample_entity_whole_population`	10000	-1.617%	-2.280%	-0.958%
algorithm_benches	`algorithm_sampling_single_known_length`		-1.206%	-1.637%	-0.889%
indexing	`query_people_count_indexed_multi-property_entities`		-1.131%	-1.354%	-0.876%
large_dataset	`bench_query_population_indexed_property_entities`		-1.065%	-1.615%	-0.524%
large_dataset	`bench_query_population_multi_indexed_entities`		-1.016%	-1.783%	-0.332%
examples	`example-basic-infection`		-1.013%	-1.422%	-0.614%
sampling	`count_and_sampling_single_unindexed_concrete_plus_derived_entiti`		-0.837%	-1.109%	-0.593%
sampling	`sampling_multiple_known_length_entities`		0.722%	0.080%	1.454%
sampling	`sampling_single_unindexed_concrete_plus_derived_entities`		0.704%	0.330%	1.055%
counts	`multi_property_unindexed_entities`		0.575%	0.289%	0.980%
sample_entity	`sample_entity_whole_population`	100000	-0.539%	-1.100%	0.017%
counts	`concrete_plus_derived_unindexed_entities`		0.489%	-0.206%	1.339%
algorithm_benches	`algorithm_sampling_multiple_l_reservoir`		0.418%	0.212%	0.641%
algorithm_benches	`algorithm_sampling_single_l_reservoir`		0.370%	0.075%	0.588%
sampling	`count_and_sampling_single_known_length_entities`		0.348%	-0.179%	0.746%
large_dataset	`bench_filter_indexed_entity`		-0.343%	-8.593%	8.263%
algorithm_benches	`algorithm_sampling_single_rand_reservoir`		0.330%	0.219%	0.435%
indexing	`with_query_results_multiple_individually_indexed_properties_enti`		-0.285%	-0.960%	0.145%
large_dataset	`bench_query_population_property_entities`		-0.237%	-0.741%	0.117%
sampling	`sampling_single_known_length_entities`		0.143%	-0.416%	0.587%
sampling	`sampling_multiple_l_reservoir_entities`		0.095%	-0.078%	0.274%
counts	`multi_property_indexed_entities`		-0.058%	-0.876%	1.015%
algorithm_benches	`algorithm_sampling_multiple_known_length`		-0.055%	-0.487%	0.329%
indexing	`with_query_results_indexed_multi-property_entities`		-0.037%	-0.220%	0.168%
counts	`single_property_unindexed_entities`		-0.013%	-0.550%	0.513%

swo · 2026-04-21T18:38:38Z

@bbbruce -- Robert asked for another pair of eyes on this example. Would you take a look? I could do a more full-blown analysis to check for correctness if we consider the prior state to be a gold standard.

swo · 2026-04-28T17:01:23Z

@bbbruce I reworked a little bit as per our discussion:

Don't use network module; instead define an Edge entity
I define Node1 and Node2 as two separate properties. (My first instinct was to define Nodes(node1, node2), but I couldn't figure out how to context.query() for only part of a tuple property, like .query(with!(Edge, Nodes(_, some_person))).)
I opted for directional edges, which make the queries easier (rather than unidirectional edges, which requires half the entities but makes the queries more complicated).
I'm having trouble figuring out how to test this. I'd like to say "look for person with data ID 826. They should have 5 contacts." That requires me to (1) query a Person, (2) get their PersonId, and (3) use that PersonId to find the relevant edges. Step 2 has me stumped. Any ideas?

github-actions · 2026-04-28T17:05:17Z

Benchmark Results

Hyperfine

Command	Mean [ms]	Min [ms]	Max [ms]	Relative
`large_sir::baseline`	2.4 ± 0.2	2.3	3.8	1.00
`large_sir::entities`	9.7 ± 0.1	9.5	10.0	4.01 ± 0.35

Criterion

Regressions (slower)

Group	Bench	Param	Change	CI Lower	CI Upper
large_dataset	`bench_query_population_multi_indexed_entities`		58.220%	56.884%	59.430%
sample_entity	`sample_entity_single_property_unindexed`	10000	55.604%	55.136%	56.066%
counts	`multi_property_indexed_entities`		54.628%	53.705%	55.398%
sampling	`count_and_sampling_single_unindexed_concrete_plus_derived_entiti`		40.148%	38.424%	41.800%
sample_entity	`sample_entity_multi_property_indexed`	100000	32.269%	31.962%	32.596%
sample_entity	`sample_entity_multi_property_indexed`	10000	31.433%	31.019%	32.111%
sample_entity	`sample_entity_multi_property_indexed`	1000	31.427%	30.769%	32.076%
indexing	`with_query_results_indexed_multi-property_entities`		28.066%	27.065%	28.816%
indexing	`query_people_count_indexed_multi-property_entities`		24.021%	23.535%	24.424%
sampling	`sampling_single_unindexed_concrete_plus_derived_entities`		22.737%	18.670%	26.591%
large_dataset	`bench_query_population_multi_unindexed_entities`		9.687%	7.902%	11.598%
examples	`example-basic-infection`		5.794%	4.893%	6.617%
sampling	`sampling_multiple_known_length_entities`		2.959%	2.095%	3.702%
sampling	`sampling_single_known_length_entities`		2.236%	1.406%	3.006%
sampling	`sampling_single_l_reservoir_entities`		1.794%	1.189%	2.542%

Improvements (faster)

Group	Bench	Param	Change	CI Lower	CI Upper
indexing	`with_query_results_single_indexed_property_entities`		-14.431%	-14.662%	-14.195%
indexing	`query_people_single_indexed_property_entities`		-13.997%	-14.121%	-13.864%
indexing	`query_people_count_single_indexed_property_entities`		-12.092%	-12.462%	-11.825%
large_dataset	`bench_filter_unindexed_entity`		-11.850%	-14.385%	-9.138%
large_dataset	`bench_match_entity`		-11.085%	-11.408%	-10.619%
sample_entity	`sample_entity_single_property_indexed`	100000	-9.837%	-10.161%	-9.584%
sample_entity	`sample_entity_single_property_indexed`	1000	-9.780%	-10.062%	-9.529%
sample_entity	`sample_entity_single_property_indexed`	10000	-9.369%	-9.564%	-9.134%
examples	`example-births-deaths`		-8.775%	-9.547%	-8.156%
large_dataset	`bench_query_population_derived_property_entities`		-4.910%	-5.784%	-4.090%
sampling	`sampling_single_unindexed_entities`		-4.661%	-4.822%	-4.502%
counts	`reindex_after_adding_more_entities`		-4.476%	-4.626%	-4.326%
indexing	`query_people_indexed_multi-property_entities`		-3.672%	-4.039%	-3.394%
sample_entity	`sample_entity_single_property_unindexed`	1000	-2.657%	-2.947%	-2.336%
indexing	`with_query_results_multiple_individually_indexed_properties_enti`		-1.999%	-2.184%	-1.784%
sampling	`sampling_multiple_unindexed_entities`		-1.690%	-2.316%	-1.059%

Unchanged / inconclusive (CI crosses 0%)

Group	Bench	Param	Change	CI Lower	CI Upper
large_dataset	`bench_query_population_property_entities`		-1.367%	-2.368%	-0.543%
counts	`concrete_plus_derived_unindexed_entities`		-1.234%	-1.614%	-0.945%
sample_entity	`sample_entity_whole_population`	1000	-1.230%	-1.641%	-0.925%
sample_entity	`sample_entity_single_property_unindexed`	100000	1.156%	0.849%	1.412%
indexing	`query_people_multiple_individually_indexed_properties_entities`		1.138%	0.673%	1.498%
counts	`single_property_indexed_entities`		-1.105%	-1.901%	-0.401%
algorithm_benches	`algorithm_sampling_multiple_l_reservoir`		1.052%	0.735%	1.393%
sampling	`sampling_multiple_l_reservoir_entities`		-0.954%	-2.068%	-0.017%
large_dataset	`bench_filter_indexed_entity`		0.873%	-6.322%	9.397%
sample_entity	`sample_entity_whole_population`	10000	-0.793%	-1.047%	-0.497%
large_dataset	`bench_query_population_indexed_property_entities`		0.717%	0.355%	1.168%
algorithm_benches	`algorithm_sampling_single_known_length`		-0.533%	-1.394%	0.233%
sample_entity	`sample_entity_whole_population`	100000	-0.533%	-0.974%	-0.204%
algorithm_benches	`algorithm_sampling_multiple_known_length`		-0.405%	-0.776%	0.161%
indexing	`query_people_count_multiple_individually_indexed_properties_enti`		-0.331%	-0.523%	-0.134%
sampling	`count_and_sampling_single_known_length_entities`		0.310%	-0.426%	1.069%
counts	`multi_property_unindexed_entities`		-0.282%	-0.617%	0.171%
counts	`single_property_unindexed_entities`		0.271%	-0.094%	0.719%
algorithm_benches	`algorithm_sampling_single_l_reservoir`		-0.232%	-0.471%	0.081%
counts	`index_after_adding_entities`		0.156%	-0.106%	0.528%
algorithm_benches	`algorithm_sampling_single_rand_reservoir`		-0.143%	-0.862%	0.680%

Put contacts into network file

64a6698

swo force-pushed the swo_doc_hh_example branch from 652087b to 64a6698 Compare April 16, 2026 18:14

fixup

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Update bench-history.json (PR #847 @ 64a6698)

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fixup: linting

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swo added 2 commits April 20, 2026 12:02

bug: expose only the susceptible

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Consider changes to network structure #250

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docs: network-hhmodel example: Separate contact from disease progression#847

docs: network-hhmodel example: Separate contact from disease progression#847
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Benchmark Results

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