def METHOD_NAME():
    region_tx = Region.from_state("TX")
    region_sf = Region.from_fips("06075")
    region_ma = Region.from_state("MA")
    # TX has metrics that will be transformed to a percent of the population. Include some other
    # data to make sure it is not dropped.
    tx_timeseries_in = {
        CommonFields.VACCINATIONS_INITIATED: TimeseriesLiteral(
            [1_000, 2_000],
            annotation=[test_helpers.make_tag(date="2020-04-01")],
            provenance=["prov1"],
        ),
        CommonFields.VACCINATIONS_COMPLETED: [None, 1_000],
        CommonFields.VACCINATIONS_ADDITIONAL_DOSE: [1_000, 5_000],
        CommonFields.VACCINATIONS_2022_FALL_BIVALENT_DOSE: [1_000, 5_000],
        CommonFields.CASES: TimeseriesLiteral([1, 2], provenance=["caseprov"]),
    }
    # MA metrics will be transformed and capped at 95% after exceeding 95,000 doses
    ma_timeseries_in = {
        CommonFields.VACCINATIONS_INITIATED: TimeseriesLiteral(
            [94_000, 96_000],
            annotation=[test_helpers.make_tag(date="2020-04-01")],
            provenance=["prov1"],
        ),
        CommonFields.CASES: TimeseriesLiteral([1, 2], provenance=["caseprov"]),
    }
    # SF does not have any vaccination metrics that can be transformed to a percentage so for it
    # the input and output are the same, except 97% is capped to 95%.
    sf_timeseries = {
        CommonFields.VACCINATIONS_COMPLETED_PCT: [10, 97],
    }
    static_data_map = {
        region_tx: {CommonFields.POPULATION: 100_000},
        region_sf: {CommonFields.POPULATION: 10_000},
        region_ma: {CommonFields.POPULATION: 100_000},
    }
    ds_in = test_helpers.build_dataset(
        {region_tx: tx_timeseries_in, region_sf: sf_timeseries, region_ma: ma_timeseries_in},
        static_by_region_then_field_name=static_data_map,
    )
    ds_out = vaccine_backfills.derive_vaccine_pct(ds_in)
    ds_expected = test_helpers.build_dataset(
        {
            region_tx: {
                **tx_timeseries_in,
                CommonFields.VACCINATIONS_INITIATED_PCT: [1, 2],
                CommonFields.VACCINATIONS_COMPLETED_PCT: [None, 1],
                CommonFields.VACCINATIONS_ADDITIONAL_DOSE_PCT: [1, 5],
                CommonFields.VACCINATIONS_BIVALENT_DOSE_PCT: [1, 5],
            },
            region_ma: {**ma_timeseries_in, CommonFields.VACCINATIONS_INITIATED_PCT: [94, 95],},
            region_sf: {CommonFields.VACCINATIONS_COMPLETED_PCT: [10, 95],},
        },
        static_by_region_then_field_name=static_data_map,
    )
    test_helpers.assert_dataset_like(ds_out, ds_expected)