The National Child Abuse and Neglect Data System (NCANDS) Child File data set consists of child-specific data of all reports of maltreatment to State child protective service agencies that received an investigation or assessment response. NCANDS is a Federally-sponsored national data collection effort created for the purpose of tracking the volume and nature of child maltreatment reporting each year within the United States. The Child File is the case-level component of the NCANDS. Child File data are collected annually through the voluntary participation of States. Participating States submit their data after going through a process in which the State's administrative system is mapped to the NCANDS data structure. Data elements include the demographics of children and their perpetrators, types of maltreatment, investigation or assessment dispositions, risk factors, and services provided as a result of the investigation or assessment.

These data were modeled using multiple sources of input data (see below) to infer the most likely learning modality of a school district for a given week. These data should be considered district-level estimates and may not always reflect true learning modality, particularly for districts in which data are unavailable. If a district reports multiple modality types within the same week, the modality offered for the majority of those days is reflected in the weekly estimate. All school district metadata are sourced from the National Center for Educational Statistics (NCES) for 2020-2021.

School learning modality types are defined as follows:

• In-Person: All schools within the district offer face-to-face instruction 5 days per week to all students at all available grade levels.


• Remote: Schools within the district do not offer face-to-face instruction; all learning is conducted online/remotely to all students at all available grade levels.


• Hybrid: Schools within the district offer a combination of in-person and remote learning; face-to-face instruction is offered less than 5 days per week, or only to a subset of students.

• School learning modality data provided here are model estimates using combined input data and are not guaranteed to be 100% accurate. This learning modality dataset was generated by combining data from four different sources: Burbio [1], MCH Strategic Data [2], the AEI/Return to Learn Tracker [3], and state dashboards [4-20]. These data were combined using a Hidden Markov model which infers the sequence of learning modalities (In-Person, Hybrid, or Remote) for each district that is most likely to produce the modalities reported by these sources. This model was trained using data from the 2020-2021 school year. Metadata describing the location, number of schools and number of students in each district comes from NCES [21].


• You can read more about the model in the CDC MMWR: COVID-19–Related School Closures and Learning Modality Changes — United States, August 1–September 17, 2021.


• The metrics listed for each school learning modality reflect totals by district and the number of enrolled students per district for which data are available. School districts represented here exclude private schools and include the following NCES subtypes:
  
  
  
  • Public school district that is NOT a component of a supervisory union
  
  
  • Public school district that is a component of a supervisory union
  
  
  • Independent charter district
  
  
  
  


• “BI” in the state column refers to school districts funded by the Bureau of Indian Education.

• Data from August 1, 2021 to June 24, 2022 correspond to the 2021-2022 school year. During this time frame, data from the AEI/Return to Learn Tracker and most state dashboards were not available. Inferred modalities with a probability below 0.6 were deemed inconclusive and were omitted. During the Fall 2022 semester, modalities for districts with a school closure reported by Burbio were updated to either “Remote”, if the closure spanned the entire week, or “Hybrid”, if the closure spanned 1-4 days of the week.


• Data from August

These data were modeled using multiple sources of input data (see below) to infer the most likely learning modality of a school district for a given week. These data should be considered district-level estimates and may not always reflect true learning modality, particularly for districts in which data are unavailable. If a district reports multiple modality types within the same week, the modality offered for the majority of those days is reflected in the weekly estimate. All school district metadata are sourced from the National Center for Educational Statistics (NCES) for 2020-2021.

School learning modality types are defined as follows:

• In-Person: All schools within the district offer face-to-face instruction 5 days per week to all students at all available grade levels.


• Remote: Schools within the district do not offer face-to-face instruction; all learning is conducted online/remotely to all students at all available grade levels.


• Hybrid: Schools within the district offer a combination of in-person and remote learning; face-to-face instruction is offered less than 5 days per week, or only to a subset of students.

• School learning modality data provided here are model estimates using combined input data and are not guaranteed to be 100% accurate. This learning modality dataset was generated by combining data from four different sources: Burbio [1], MCH Strategic Data [2], the AEI/Return to Learn Tracker [3], and state dashboards [4-20]. These data were combined using a Hidden Markov model which infers the sequence of learning modalities (In-Person, Hybrid, or Remote) for each district that is most likely to produce the modalities reported by these sources. This model was trained using data from the 2020-2021 school year. Metadata describing the location, number of schools and number of students in each district comes from NCES [21].


• You can read more about the model in the CDC MMWR: COVID-19–Related School Closures and Learning Modality Changes — United States, August 1–September 17, 2021.


• The metrics listed for each school learning modality reflect totals by district and the number of enrolled students per district for which data are available. School districts represented here exclude private schools and include the following NCES subtypes:
  
  
  
  • Public school district that is NOT a component of a supervisory union
  
  
  • Public school district that is a component of a supervisory union
  
  
  • Independent charter district
  
  
  
  


• “BI” in the state column refers to school districts funded by the Bureau of Indian Education.

• Data from September 1, 2020 to June 25, 2021 correspond to the 2020-2021 school year. During this timeframe, all four sources of data were available. Inferred modalities with a probability below 0.75 were deemed inconclusive and were omitted.


• Data for the month of July may show “In Person” status although most school districts are effectively closed during this time for summer break. Users may wish to exclude July data from use for this reason where applicable.

1. K-12 School Opening Tracker. Burbio 2021; https

The National Child Abuse and Neglect Data System (NCANDS) Child File data set consists of child-specific data of all reports of maltreatment to State child protective service agencies that received an investigation or assessment response. NCANDS is a Federally-sponsored national data collection effort created for the purpose of tracking the volume and nature of child maltreatment reporting each year within the United States. The Child File is the case-level component of the NCANDS. Child File data are collected annually through the voluntary participation of States. Participating States submit their data after going through a process in which the State's administrative system is mapped to the NCANDS data structure. Data elements include the demographics of children and their perpetrators, types of maltreatment, investigation or assessment dispositions, risk factors, and services provided as a result of the investigation or assessment.

The National Child Abuse and Neglect Data System (NCANDS) Child File data set consists of child-specific data of all reports of maltreatment to State child protective service agencies that received an investigation or assessment response. NCANDS is a Federally-sponsored national data collection effort created for the purpose of tracking the volume and nature of child maltreatment reporting each year within the United States. The Child File is the case-level component of the NCANDS. Child File data are collected annually through the voluntary participation of States. Participating States submit their data after going through a process in which the State's administrative system is mapped to the NCANDS data structure. Data elements include the demographics of children and their perpetrators, types of maltreatment, investigation or assessment dispositions, risk factors, and services provided as a result of the investigation or assessment.