Kenya recorded 343074 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Kenya reported 5668 Coronavirus Deaths. This dataset includes a chart with historical data for Kenya Coronavirus Cases.

Kenya KE: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 13.400 % in 2016. This records an increase from the previous number of 13.300 % for 2015. Kenya KE: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 13.400 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 17.300 % in 2000 and a record low of 13.300 % in 2015. Kenya KE: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted Average;

Kenya KE: Death Rate: Crude: per 1000 People data was reported at 5.732 Ratio in 2016. This records a decrease from the previous number of 5.841 Ratio for 2015. Kenya KE: Death Rate: Crude: per 1000 People data is updated yearly, averaging 11.541 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 20.207 Ratio in 1960 and a record low of 5.732 Ratio in 2016. Kenya KE: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Abstract

The Kilifi Health and Demographic Surveillance System (KHDSS), located on the Indian Ocean coast of Kenya, was established in 2000 as a record of births, pregnancies, migration events, deaths and cause of deaths and is maintained by 4-monthly household visits. The study area was selected to capture the majority of patients admitted to Kilifi District Hospital. The KHDSS has 284 000 residents and covers 891 km2 and the hospital admits 4400 paediatric patients and 3400 adult patients per year. At the hospital, morbidity events are linked in real time by a computer search of the population register. Linked surveillance was extended to KHDSS vaccine clinics in 2008.

KHDSS data have been used to define the incidence of hospital presentation with childhood infectious diseases (e.g. rotavirus diarrhoea, pneumococcal disease), to test the association between genetic risk factors (e.g. thalassaemia and sickle cell disease) and infectious diseases, to define the community prevalence of chronic diseases (e.g. epilepsy), to evaluate access to health care and to calculate the operational effectiveness of major public health interventions (e.g. conjugate Haemophilus influenzae type b vaccine). Rapport with residents is maintained through an active programme of community engagement. A system of collaborative engagement exists for sharing data on survival, morbidity, socio-economic status and vaccine coverage.

Geographic coverage

Kilifi District is situated 60km to the north of Mombasa on the Kenyan coast. It has an area of approximately 2,500 square kilometres and a population of 650,000. A flat coastal strip extends approximately 10km inland to low hills rising to an altitude of 250 metres

An area of 891 km2 was selected as the smallest number of administrative sublocations that collectively included the stated sublocation of residence of at least 80% of paediatric inpatients in the preceding 3 years (1998-2000). KDH is located in Kilifi town, 3° south of the equator and KHDSS extends up and down the coastal strip for 35 km from Kilifi. KDH is the only inpatient facility offering paediatric services in the KHDSS area. The local economy is based on subsistence farming of maize, cassava, cashew nuts and coconuts as well as goats and dairy cows. Two large agricultural estates, two research institutes and several tourist hotels contribute to local employment.

Analysis unit

Individual

Universe

All individuals in the HDSS area

Frequency of data collection

Three rounds in a year

Sampling procedure

No sampling, complete population surveyed

Sampling deviation

Not Applicable

Mode of data collection

Proxy Respondent [proxy]

Research instrument

1. Enumeration of persons

The Enumeration of People Data Entry Form has all names of residents within an homestead (Hm). This form bears the Enumeration Zone ( EZ) and Hm numbers, Hm name and name of homesteadhead. Also, it has details of each individual such as name, sex, ethinicity, pregnancy status, Kenya national identification number, Mother's national identification card number as well as the BU where an individual sleeps. A Fw uses this form to up-date the residence status of people.

1. Enumeration of buildings

This form has a list of all homesteads and existing buildings in each homestead (Hm). The form indicates: Hm name, Hm number and building units(BUs) in alphabet numbers. The geographical co-ordinates and materials used to make each building are also included. The census FWs update this form to show if the building unit still exists or if the BU has been demolished.

1. Listing of all registered Homesteads The Listing of All Registered Homesteads form has all active Hms in a sub-enumeration zone (sub- EZ) according to the previous census round. It is used to confirm number and specific HMs in a sub-EZ with the records of Building Structure (BS) Data Entry Form

2. In migrants

This form is used to record new people who have moved into an existing or a new homestead, or people who have been present but missed in the previous census rounds and intend to stay for the next three or more months.

5 .Births

This form is used to record all new born babies by resident mothers. In this form, all personal details of the baby are recorded and linked to those of the mother if she is a resident.

1. Pregnancy All resident women within the reproductive age bracket i.e., between 15 and 49 years, are usually flagged in the Enumeration Data Entry form to be asked about their pregnancy status.

2. Change person details Change Personal Details Data Entry form is designed to record changes of personal details.The Change Personal Details Data Entry form provides fields and codes used to effect such changes or corrections. Accuracy of the new value must be supported by evidence, preferrably documented evidence for example, a national identification card for date of birth.

8 .Change buildings details The change buildings details data entry form is designed to record changes relating to building materials, category and coordinates of a building unit as well as change of homestead names. Potential areas for changes and corrections include the Hm name, roof, wall, storey, longitudes, latitudes and elevation. Specific codes are used to describe the type of a building characteristic to be changed.

1. Maps KHDSS enumerators use EZ maps with a list of Hms that bears coresponding Hm numbers. Vital landmarks, roads and other features are displayed on a map to assist locate and identify Hms. These maps are up-dated every census round by the mapping team and enumerators. Global Positioning System (GPS) and Geographic Information System (GIS) technologies are used to develop and maintain a mapping database. ETrex garmin GPS receivers are used to collect spatial data and ArcGIS 10 is used to manipulate, edit, store and generate maps.

10.Verbal autopsy

11.Extra Questions

Cleaning operations

Manual editing A manual editor on daily basis checks completed tools for completeness and consistency. Those that have issues are returned to the responsible fieldworkers for correction and/or follow ups. Manual editor’s reports are instrumental in evaluating fieldworkers after every two weeks.

Complementary nature of KEMRI studies Kemri-Wellcome Trust Programme has a number of research studies being conducted in the same KHDSS census area. Some of these studies are nested within the KHDSS and have proved useful in improving data quality. For example, issues have been raised concerning some details such as date of birth and sex, which prompted verifications in the field and corrections.

The following processing checks are done during the ETL process.

1. If the first event is legal. Like the first event must beenumeration, birth or inmigration.
2. If the last event is legal. Like the last event must be end of observtion, death or outmigration.

3. If the transition events are legal. The list of legal transitions:

   Birth followed by death Birth followed by exit Birth followed by end of observation Birth followed by outmigration

   Death followed by none

   Entry followed by death Entry followed by exit Entry followed by end of observation Entry followed by outmigration Enumeration followed by death Enumeration followed by exit Enumeration followed by outmigration

   Exit followed by entry

   Inmigration followed by Death Inmigration followed by exit Inmigration followed by end of observation Inmigration followed by outmigration

   End of observation followed by none

   Outmigration followed by none Outmigration followed by enumeration Outmigration followed by inmigration

   The list of illegal transitions:

   Birth followed by none Birth followed by birth Birth followed by entry Birth followed by enumeration Birth followed by inmigration

   Death followed by birth Death followed by death Death followed by entry Death followed by enumeration Death followed by exit Death followed by inmigration Death followed by outmigration Death followed by end of observation

   Entry followed by none Entry followed by birth Entry followed by entry Entry followed by enumeration Entry followed by inmigration

   Enumeration followed by none Enumeration followed by birth Enumeration followed by entry Enumeration followed by enumeration Enumeration followed by inmigration

   Exit followed by birth Exit followed by death Exit followed by exit Exit followed by end of observation Exit followed by outmigration

   Inmigration followed by none Inmigration followed by birth Inmigration followed by entry Inmigration followed by enumeration Inmigration followed by inmigration

   End of observation followed by birth End of observation followed by death End of observation followed by entry End of observation followed by enumeration End of observation followed by exit End of observation followed by inmigration End of observation followed by end of observation End of observation followed by outmigration

   Outmigration followed by birth Outmigration followed by death Outmigration followed by exit Outmigration followed by end of observation Outmigration followed by outmigration

   List of edited events:

   Exit followed by none Exit followed by enumeration Exit followed by inmigration Outmigration followed by entry

Response

UNICEF's country profile for Kenya, including under-five mortality rates, child health, education and sanitation data.

As of July 4, 2022, Kenya had over 334,500 cumulative confirmed cases of coronavirus (COVID-19). The number of casualties were at some 5,650, while the recoveries amounted to over 325,400. The capital Nairobi registered the highest number of cases in Kenyan counties.

Abstract

The places we live affect our health status and the choices and opportunities we have (or do not have) to lead fulfilling lives. Over the past ten years, the African Population & Health Research Centre (APHRC) has led pioneering work in highlighting some of the major health and livelihood challenges associated with rapid urbanization in sub-Saharan Africa (SSA). In 2002, the Centre established the first longitudinal platform in urban Africa in the city of Nairobi in Kenya. The platform known as the Nairobi Urban Health and Demographic Surveillance System collects data on two informal settlements - Korogocho and Viwandani - in Nairobi City every four months on issues ranging from household dynamics to fertility and mortality, migration and livelihood as well as on causes of death, using a verbal autopsy technique. The dataset provided here contains key demographic and health indicators extracted from the longitudinal database. Researchers interested in accessing the micro-data can look at our data access policy and contact us.

Geographic coverage

The Demographic Surveillance Area (combining Viwandani and Korogocho slum settlements) covers a land area of about 0.97 km2, with the two informal settlements located about 7 km from each other. Korogocho is located 12 km from the Nairobi city center; in Kasarani division (now Kasarani district), while Viwandani is about 7 km from Nairobi city center in Makadara division (now Madaraka district). The DSA covers about seven villages each in Korogocho and Viwandani.

Analysis unit

Individual

Universe

Between 1st January and 31st December,2015 the Nairobi HDSS covered 86,304 individualis living in 30,219 households distributed across two informal settlements(Korogocho and Viwandani) were observed. All persons who sleep in the household prior to the day of the survey are included in the survey, while non-resident household members are excluded from the survey.

The present universe started out through an initial census carried out on 1st August,2002 of the population living in the two Informal settlements (Korogocho and Viwandani). Regular visits have since then been made (3 times a year) to update information on births, deaths and migration that have occurred in the households observed at the initial census. New members join the population through a birth to a registered member, or an in-migration, while existing members leave through a death or out-migration. The DSS adopts the concept of an open cohort that allows new members to join and regular members to leave and return to the system.

Kind of data

Event history data

Frequency of data collection

Three rounds in a year

Sampling procedure

This dataset is related to the whole demographic surveillance area population. The number of respondents has varied over the last 13 years (2002-2015), with variations being observed at both household level and at Individual level. As at 31st December 2015, 66,848 were being observed under the Nairobi HDSS living in 25,812 households distributed across two informal settlements(Korogocho and Viwandani). The variable IndividualId uniquely identifies every respondent observed while the variable LocationId uniquely identifies the room in which the individual was living at any point in time. To identify individuals who were living together at any one point in time (a household) the data can be split on location and observation dates.

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

Questionnaires are printed and administered in Swahili, the country's national language.

The questionnaires for the Nairobi HDSS were structured questionnaires based on the INDEPTH Model Questionnaire and were translated into Swahili with some modifications and additions.After an initial review the questionnaires were translated back into English by an independent translator with no prior knowledge of the survey. The back translation from the Swahili version was independently reviewed and compared to the English original. Differences in translation were reviewed and resolved in collaboration with the original translators. The English and Swahili questionnaires were both piloted as part of the survey pretest.

At baseline, a household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. In later rounds questionnaires to track the migration of the population observed at baseline, and additonal questionnaires to capture demographic and health events happening to the population have been introduced.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of STATA data files

Where changes were made by the program, a cold deck imputation is preferred; where incorrect values were imputed using existing data from another dataset. If cold deck imputation was found to be insufficient, hot deck imputation was used, In this case, a missing value was imputed from a randomly selected similar record in the same dataset.

Some corrections are made automatically by the program(80%) and the rest by visual control of the questionnaires (20%).

1. 100% forms filled in by FRAs are rechecked for completeness, ensured that all the necessary event forms are filled in.
2. Spot checks are done on field over data collection by FRAs for reliability of data.
3. FRS instructs revisits wherever required.
4. Forms are checked on sample basis
5. Checks if all the necessary event forms are filled in.
6. Forms with inconsistencies identified at the time of entry are sent back to the field.
7. Creating and managing data entry checks for picking up inconsistencies
8. Monitoring field work: balancing work target and quality.
9. Dealing with data inconsistencies at data level and giving feedbacks to field staff.
10. Conducting training and refresher training wherever required.
11. Data cleaning

Response rate

Over the years the response rate at household level has varied between 95% and 97% with response rate at Individual Level varying between 92% and 95%. Challenges to acheiving a 100% response rate have included: - high population mobility within the study area - high population attrition - respondent fatigue - security in some areas

Sampling error estimates

Not applicable for surveillance data

Data appraisal

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate KE031 MicroDataCleaned Starts 219285 2017-05-16 18:25
KE031 MicroDataCleaned Transitions 825036 825036 0 2017-05-16 18:25
KE031 MicroDataCleaned Ends 219285 2017-05-16 18:25
KE031 MicroDataCleaned SexValues 825036 2017-05-16 18:25
KE031 MicroDataCleaned DoBValues 42 824994 825036 0 2017-05-16 18:25

In 2022, nearly 3.42 million cases of malaria were confirmed in Kenya. Although the number of reported infections, including presumed and confirmed cases, declined from over five million in 2019, the disease is still one of the main health issues in the country. Some 219 deaths due to malaria were registered in Kenya as of 2022.