Package index • sntmethods

DHS survey indicators

Survey-weighted, design-correct estimates from DHS/MIS microdata. Each returns long-format admin-level tables with confidence intervals and design effects.

calc_itn_dhs(): Calculate ITN Indicators from DHS Data
calc_irs_dhs(): Calculate IRS Coverage from DHS Data
calc_pfpr_dhs(): Calculate PfPR Indicators from DHS Data
calc_act_dhs(): Calculate ACT Treatment Indicators from DHS Data
calc_antimalarial_dhs(): Calculate Antimalarial Treatment from DHS Data (Standardized)
calc_fever_dhs(): Calculate Fever Prevalence from DHS Data
calc_malaria_dx_dhs(): Calculate Malaria Diagnostic Testing from DHS Data (Standardized)
calc_case_management_dhs(): Calculate Effective Coverage of Case Management from DHS Data
calc_anc_dhs(): Calculate ANC Coverage from DHS Data (standardized long-format output)
calc_iptp_dhs(): Calculate IPTp Coverage from DHS Data (standardized long-format output)
calc_epi_dhs(): Calculate EPI Coverage from DHS Data (Standardized)
calc_smc_dhs(): Calculate SMC Coverage from DHS Data
calc_severe_anemia_dhs(): Calculate Severe Anemia Prevalence from DHS Data (Standardized)
calc_u5mr_dhs(): Calculate U5MR from DHS Data (Standardized Long Format)
calc_csb_dhs(): Calculate Care-Seeking Behavior from DHS Data ( Methodology)
calc_csb_by_wealth_dhs(): Calculate Care-Seeking Behavior by Wealth Quintile from DHS Data
calc_wealth_dhs(): Calculate Wealth Quintile Distributions from DHS Data
calculate_dhs_gini(): Calculate Gini Coefficient Using DHS Brown Formula Methodology

DHS data access and dictionaries

Read DHS parquet archives, inspect variable labels, and look up indicator metadata.

dhs_read(): Read a DHS recode from a hive-partitioned parquet archive
dhs_dictionary(): Master DHS Indicator Dictionary
dhs_model_datasets(): Get DHS Model Dataset URLs and Metadata
make_dhs_raw_dictionary(): Create Data Dictionary for DHS Raw Datasets
list_dhs_var_labels(): List DHS variables and their haven labels by name pattern
join_dhs_coords(): Join DHS GPS Coordinates to Person Records Data

MBG pipeline and modeling

Model-based geostatistics workflow - from cluster data to fitted models, prediction rasters and population-weighted admin estimates.

run_mbg_pipeline(): Run MBG Indicator Pipeline
mbg_pipeline run_mbg_indicator_pipeline: MBG Indicator Pipeline
fit_mbg_indicator(): Fit a Single MBG Indicator (Generic, Pluggable Admin Levels)
build_final_dataset(): Build Final ADM2 Dataset
aggregate_raster_to_admin(): Aggregate Raster to Administrative Level
save_mbg_cluster_data(): Save MBG Cluster Data
save_mbg_rasters(): Save MBG Rasters

MBG cluster-data preparation

Prepare cluster-level inputs for each indicator family used by the MBG pipeline.

calc_itn_mbg(): Prepare ITN Data for MBG Analysis
calc_irs_mbg(): Prepare IRS Data for MBG Analysis
calc_pfpr_mbg(): Prepare PfPR Data for MBG Analysis
calc_act_mbg(): Prepare ACT and Antimalarial Data for MBG Analysis
calc_antimalarial_mbg(): Prepare Antimalarial Treatment Data for MBG Analysis
calc_fever_mbg(): Prepare Fever Prevalence Data for MBG Analysis
calc_malaria_dx_mbg(): Prepare Malaria Diagnostic Testing Data for MBG Analysis
calc_anc_mbg(): Prepare ANC Data for MBG Analysis
calc_iptp_mbg(): Prepare IPTp Data for MBG Analysis
calc_epi_mbg(): Prepare EPI (Vaccination) Data for MBG Analysis
calc_smc_mbg(): Prepare SMC Data for MBG Analysis
calc_anemia_mbg(): Prepare Anemia Data for MBG Analysis
calc_u5mr_mbg(): Prepare U5MR Data for MBG Analysis
calc_csb_mbg(): Prepare Care-Seeking Behavior Data for MBG Analysis
calc_csb_by_wealth_mbg(): Prepare Care-Seeking Behavior Data by Wealth Quintile for MBG Analysis
calc_wealth_mbg(): Prepare Wealth Quintile Distribution Data for MBG Analysis
prep_itn_mbg(): Prepare Single ITN Indicator for MBG
prep_irs_mbg(): Prepare IRS Data for MBG (Alias)
prep_pfpr_mbg(): Prepare Single PfPR Indicator for MBG
prep_act_mbg(): Prepare Single ACT Indicator for MBG
prep_antimalarial_mbg(): Prepare Single Antimalarial Indicator for MBG
prep_fever_mbg(): Prepare Single Fever Indicator for MBG
prep_malaria_dx_mbg(): Prepare Single Malaria Dx Indicator for MBG
prep_anc_mbg(): Prepare Single ANC Indicator for MBG
prep_iptp_mbg(): Prepare Single IPTp Indicator for MBG
prep_epi_mbg(): Prepare Single EPI Indicator for MBG
prep_smc_mbg(): Prepare SMC Data for MBG (Alias)
prep_anemia_mbg(): Prepare Single Anemia Indicator for MBG
prep_csb_mbg(): Prepare Single CSB Indicator for MBG
prep_csb_by_wealth_mbg(): Prepare Single CSB Indicator by Wealth Quintile for MBG
prep_wealth_mbg(): Prepare Single Wealth Indicator for MBG

MBG mapping and visualization

Render indicator surfaces and cluster diagnostics from MBG outputs.

generate_all_maps(): Generate All Map Types for Indicator
generate_indicator_map(): Generate Indicator Map
save_indicator_map(): Save Indicator Map
plot_mbg_clusters(): Plot MBG Cluster Map
plot_mbg_clusters_all(): Plot All MBG Cluster Maps

Routine data - incidence

Test positivity and the N0-N5 malaria incidence cascade from routine surveillance.

calc_tpr(): Calculate Test Positivity Rate from Routine Health Facility Data
validate_tpr_proxies(): Validate TPR Proxy Quality Using Leave-One-Out Cross-Validation
calc_incidence(): Calculate Malaria Incidence from Routine Health Facility Data (N0-N5)
create_incidence(): Create an SNT Incidence Object from Tibble
check_incidence(): Check Incidence Trends

Routine data - reporting and quality

Reporting-rate metrics, facility activity classification and outlier detection.

calculate_reporting_metrics() classify_facility_activity() detect_outliers() get_active_facilities(): Re-exports from sntutils

Trend analysis

Seasonal-trend decomposition with non-parametric trend testing.

run_grouped_stl_trend(): Run STL decomposition and trend tests on grouped time series data

Utilities

Small shared helpers used across SNT pipelines.

dhs_data_path(): Resolve path inside AHADI OneDrive shared library
cmc_to_date(): Convert DHS Century Month Code to Date
normalize_zscore(): Normalize a numeric vector using z-score standardization