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Umalulu Malaria Study 2025: Interaktive Ergebnisse
In Umalulu, malaria prevention depends on what families can actually access. Explore the 2025 study of 269 households and 460 residents: mosquito-net use, housing, diagnostic access, affordability and the practical priorities emerging from the evidence.
Umalulu · East Sumba · March–July 2025
Malaria prevention must be within reach.
A net for every sleeping group. Testing close to home. The means to obtain treatment. Across 269 households and 460 interviews, this study documented the practical gaps that malaria prevention must address.
Evidence that requires action
Six findings that shape the response
Descriptive findings from the surveyed sample. Percentages below retain all module responses, including missing answers in the denominator.
Could not afford nets or antimalarial medicines
419 of 460 respondents
About this result
The question combines two purchases; it does not measure the proportion left untreated.
Explore the complete responses →Unscreened ventilation or open roof-wall gaps
203 of 269 households
About this result
122 unscreened vents + 81 open roof-wall gaps. These are housing conditions, not measured infections.
Explore the complete responses →Some or all sleeping groups did not use nets
86 of 269 households
About this result
74 reported partial use and 12 no use; one additional household did not answer.
Explore the complete responses →Lived more than 5 km from a health facility
250 of 460 respondents
About this result
Physical access remains a concern even where public insurance is widely reported.
Explore the complete responses →Did not know local mosquito breeding sites
182 of 269 household-module respondents
About this result
Knowing that mosquitoes transmit malaria does not necessarily mean recognising their habitats.
Explore the complete responses →Reported previous indoor residual spraying
3 of 269 households
About this result
200 reported never being sprayed; 66 gave no answer. Reported spraying was more than six months earlier.
Explore the complete responses →This is a malaria-risk baseline. It does not estimate current malaria prevalence, prove the cause of infection or demonstrate a reduction in disease after an intervention.
Explore the evidence
Look beyond the headline percentage
Choose from 23 indicators. Counts, denominators and unanswered questions stay visible. Household and individual modules describe different units; their percentages must not be combined as if they were linked patient records.
Can families afford nets or antimalarial medicines?
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Not enough money | 419 | 91.1% |
| Enough money | 26 | 5.7% |
| No answer | 15 | 3.3% |
This combined question does not separate the affordability of nets from medicines. It does not show that 91.1% went without treatment.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C169:C171
Mosquito-net use within households
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| All sleeping groups use nets | 182 | 67.7% |
| Some, but not all, use nets | 74 | 27.5% |
| No net use | 12 | 4.5% |
| No answer | 1 | 0.4% |
These categories count households. The 693 sleeping spaces reported in the narrative are not the denominator. Net use is reported, not directly measured protection.
Source: supplied Excel workbook · Analisa Data Lingkungan · C162:C165
Previous indoor residual spraying (IRS)
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Previously sprayed | 3 | 1.1% |
| Never sprayed | 200 | 74.3% |
| No answer | 66 | 24.5% |
Three households reported government spraying, more than six months previously. The 66 missing answers must not be classified as never sprayed. This is not a measure of current insecticide effectiveness.
Source: supplied Excel workbook · Analisa Data Lingkungan · C155:C157
Ventilation and mosquito screening
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Screened ventilation | 28 | 10.4% |
| Unscreened ventilation | 122 | 45.4% |
| Open roof-wall gaps | 81 | 30.1% |
| Closed gaps, no ventilation | 24 | 8.9% |
| Other | 3 | 1.1% |
| No answer | 11 | 4.1% |
Unscreened ventilation and open roof-wall gaps together account for 203 households (75.5%). No entomological measurement establishes how many infections resulted.
Source: supplied Excel workbook · Analisa Data Lingkungan · C69:C74
Knowledge of local mosquito breeding sites
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Knows | 81 | 30.1% |
| Does not know | 182 | 67.7% |
| No answer | 6 | 2.2% |
Household-module answers. This is a reported knowledge question, not a formal ecological assessment or a count of confirmed Anopheles breeding sites.
Source: supplied Excel workbook · Analisa Data Lingkungan · C131:C133
How long households reported using their nets
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Less than six months | 7 | 2.6% |
| Six months to one year | 3 | 1.1% |
| More than one year | 250 | 92.9% |
| No answer | 9 | 3.3% |
Duration of reported net use does not measure fabric integrity, residual insecticide activity or the age of every individual net. More than one year does not by itself mean a net is ineffective.
Source: supplied Excel workbook · Analisa Data Lingkungan · C169:C172
Knowledge of how to wash mosquito nets
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Knows | 119 | 44.2% |
| Does not know | 145 | 53.9% |
| No answer | 5 | 1.9% |
Self-reported knowledge; washing technique and insecticide retention were not tested.
Source: supplied Excel workbook · Analisa Data Lingkungan · C177:C179
Distance to the nearest health facility
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Less than 1 km | 14 | 3.0% |
| 1–5 km | 188 | 40.9% |
| More than 5 km | 250 | 54.3% |
| No answer | 8 | 1.7% |
Reported distance, not a measured journey or a demonstrated delay in receiving malaria treatment.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C130:C133
Travel time to a health facility
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Less than 15 minutes | 43 | 9.3% |
| 15–30 minutes | 239 | 52.0% |
| More than 30 minutes | 169 | 36.7% |
| No answer | 9 | 2.0% |
408 respondents (88.7%) reported at least 15 minutes. Time excludes any unmeasured wait for transport, consultation or referral.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C138:C141
Where people reported malaria testing
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Puskesmas | 36 | 7.8% |
| Hospital | 2 | 0.4% |
| At home by a village malaria cadre | 313 | 68.0% |
| Puskesmas and home by a cadre | 81 | 17.6% |
| Other | 2 | 0.4% |
| No answer | 26 | 5.7% |
394 respondents (85.7%) mentioned home testing by a cadre, including the combined category. This does not establish test quality, positivity or treatment completion.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C90:C95
Reported malaria examination method
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| RDT only | 410 | 89.1% |
| Microscopy only | 16 | 3.5% |
| RDT and microscopy | 3 | 0.7% |
| No test | 8 | 1.7% |
| No answer | 23 | 5.0% |
410 reported RDT alone; 413 (89.8%) mentioned RDT including combined responses. These are reported methods, not results of tests performed during a prevalence survey.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C82:C86
Public health-insurance coverage
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| No insurance | 25 | 5.4% |
| KIS | 324 | 70.4% |
| BPJS | 107 | 23.3% |
| No answer | 4 | 0.9% |
431 respondents (93.7%) reported KIS or BPJS. Insurance and distance are separate aggregate findings; their person-level overlap cannot be calculated.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C122:C125
Reported ease of access to malaria medicines
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Easy | 220 | 47.8% |
| Sometimes easy | 132 | 28.7% |
| Difficult | 29 | 6.3% |
| No answer | 79 | 17.2% |
161 respondents selected sometimes easy or difficult. The substantial non-response (79, 17.2%) limits interpretation; stock-outs were not independently audited.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C152:C155
Reported malaria-treatment costs
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Free | 312 | 67.8% |
| Below IDR 50,000 | 46 | 10.0% |
| IDR 50,000–100,000 | 5 | 1.1% |
| Above IDR 100,000 | 5 | 1.1% |
| No answer | 92 | 20.0% |
312 respondents reported free treatment. This does not establish that transport, lost work or all other costs were covered; 92 did not answer.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C160:C164
Night-time or early-morning activity
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| No | 174 | 37.8% |
| Yes | 283 | 61.5% |
| No answer | 3 | 0.7% |
283 respondents reported substantial activity at night or early morning. This suggests a need to address outdoor exposure; bites, species and infection risk were not measured.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C231:C233
Knowledge of malaria transmission
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Anopheles bites | 325 | 70.7% |
| Anopheles bites and needles | 1 | 0.2% |
| Unhealthy or unclean behaviour | 8 | 1.7% |
| Anopheles bites and unhealthy behaviour | 29 | 6.3% |
| Does not know | 91 | 19.8% |
| No answer | 6 | 1.3% |
355 respondents (77.2%) mentioned Anopheles across three categories. The Anopheles-only category is 325/460 (70.7%). Mentioning the vector does not establish complete understanding.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C36:C41
Usual place of defecation
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Public toilet | 15 | 5.6% |
| Private indoor toilet | 10 | 3.7% |
| Private outdoor toilet | 90 | 33.5% |
| Garden or open space | 153 | 56.9% |
| No answer | 1 | 0.4% |
Open defecation is an important sanitation and enteric-health concern. It is not proof of malaria causation. Any relation to vector exposure needs local investigation.
Source: supplied Excel workbook · Analisa Data Lingkungan · C183:C187
Standing water around the home
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| No standing water | 215 | 79.9% |
| Standing water present | 51 | 19.0% |
| No answer | 3 | 1.1% |
Observed or reported standing water is not equivalent to confirmed vector breeding. Larval identification and local vector ecology are needed.
Source: supplied Excel workbook · Analisa Data Lingkungan · C78:C80
Access to electricity
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| No electricity | 135 | 50.2% |
| PLN grid | 82 | 30.5% |
| Solar power | 46 | 17.1% |
| Other | 3 | 1.1% |
| No answer | 3 | 1.1% |
An infrastructure finding. The study did not measure the effect of electrification on malaria incidence.
Source: supplied Excel workbook · Analisa Data Lingkungan · C138:C142
Telephone and internet access
Denominator: 269 households · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| No signal | 103 | 38.3% |
| Reliable phone and internet | 33 | 12.3% |
| Intermittent phone signal | 101 | 37.5% |
| Phone only, no internet | 26 | 9.7% |
| No answer | 6 | 2.2% |
204 households (75.8%) reported no signal or intermittent signal. These conditions matter for communication, but emergency-response times were not measured.
Source: supplied Excel workbook · Analisa Data Lingkungan · C146:C150
Self-reported previous malaria
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Previously had malaria | 109 | 23.7% |
| Never had malaria | 343 | 74.6% |
| Does not know | 2 | 0.4% |
| No answer | 6 | 1.3% |
109 respondents reported ever having malaria. Reported years extend from 2012 to 2025, so this is not a five-year incidence estimate or laboratory-confirmed prevalence.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C60:C63
Reported absence from work or school
Denominator: 460 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| Never | 245 | 53.3% |
| Previously absent | 118 | 25.7% |
| No answer | 97 | 21.1% |
118 reported absence attributed to malaria, compared with 109 reporting prior malaria elsewhere. These aggregates cannot be reconciled at person level and should not be treated as a confirmed case cohort.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C177:C179
Duration among those reporting absence
Denominator: 118 respondents · All recorded categories shown
| Response | Count | Share of denominator |
|---|---|---|
| 1–3 days | 8 | 6.8% |
| 4–7 days | 99 | 83.9% |
| More than one week | 11 | 9.3% |
Conditional denominator: 118 respondents reporting absence. 110/118 (93.2%) reported at least four days. This is recalled disruption, not a medically certified duration of malaria.
Source: supplied Excel workbook · Analisa Data Pengetahuan Malari · C183:C185
Medical interpretation
A familiar disease still requires an early diagnosis
Community testing is a critical point of access
394 of 460 respondents (85.7%) mentioned malaria testing at home by a village cadre, including 81 who also mentioned a Puskesmas. This is one of the clearest operational strengths in the survey: diagnostic access already reaches homes.
The next questions are whether tests are continuously available, correctly performed, acted on promptly and followed by appropriate treatment or referral. The survey did not audit those steps.
Excel, knowledge module C90:C95 · Full report pp. 23–24
Insurance does not describe the whole journey
431 of 460 respondents (93.7%) reported public insurance, yet 250 reported living more than 5 km from care and 169 reported travel exceeding 30 minutes. These separate findings identify financial protection and physical access as different problems.
We cannot calculate how many insured individuals were also remote from care, because the supplied workbook does not link individual answers.
Excel, knowledge module C122:C141
Why timing matters clinically
Malaria is preventable and treatable, but an untreated P. falciparum infection can progress rapidly. WHO recommends parasite-based confirmation of suspected malaria using an RDT or microscopy. Severe symptoms, including impaired consciousness, repeated convulsions or difficulty breathing, require emergency care.
This general clinical context explains why nearby testing and a functioning referral pathway matter. It does not identify the parasite species or severity of any respondent’s previous illness.
WHO malaria fact sheet · Clinical context, separate from the study findings
Night-time exposure continues outside the net
283 of 460 respondents (61.5%) reported substantial night-time or early-morning activity. The field report describes farming, water collection and daily routines that take people outside. These accounts support attention to outdoor exposure, but the study did not measure mosquito biting rates or establish which activities caused infection.
Sanitation findings matter, with a different interpretation
153 of 269 households (56.9%) reported defecating in gardens or open spaces; 135 (50.2%) lacked electricity. These are substantial health and infrastructure needs. Open defecation is not itself a demonstrated cause of malaria, and the survey did not test whether latrines, electricity or water tanks reduced malaria transmission.
What previous illness and lost work can tell us
109 of 460 respondents (23.7%) reported ever having malaria; recorded years range from 2012 to 2025. This is neither five-year incidence nor current infection prevalence. Conversely, reporting no previous malaria does not establish absence of previous infection.
118 respondents reported missing work or school because of malaria, with 99 reporting four to seven days and 11 more than one week. The 118 absence reports exceed the 109 prior-malaria reports, so they cannot be interpreted as one internally verified case cohort. The livelihood burden is reported experience, without independently confirmed diagnoses or measured income loss.
From evidence to action
Six priorities that can be followed and measured
These priorities follow from the baseline and require local planning. They are proposed actions, not effects already demonstrated by this study.
1. Make complete net use possible
Evidence: 86 households reported partial or no net use; 419 individual respondents lacked purchasing capacity.
Practical response: Verify sleeping groups, inspect existing nets, supply suitable insecticide-treated nets where needed and demonstrate correct use and care.
Measure next: Proportion of sleeping groups with an available serviceable net; reported use the previous night.
2. Keep diagnosis close to households
Evidence: 394 respondents mentioned home testing by a cadre.
Practical response: Maintain RDT supplies, supportive supervision, result recording and a clear link to treatment and referral.
Measure next: Days without RDT stock; time from fever onset to testing; documented treatment or referral after a positive result.
3. Assess IRS with the malaria-control team
Evidence: Only three households reported previous spraying; 66 answers were missing.
Practical response: Review local transmission, vector behaviour, insecticide resistance and operational capacity before defining targeted IRS coverage and timing.
Measure next: Eligible structures sprayed correctly; timing and quality checks; safety and resistance monitoring.
4. Turn knowledge into practical protection
Evidence: 182 household-module respondents did not know local breeding sites; 283 individuals reported night-time activity.
Practical response: Use household demonstrations, locally appropriate exposure reduction and insect-screened ventilation that preserves airflow. Investigate potential breeding habitats with vector-control staff.
Measure next: Knowledge demonstrated in practice; verified screening improvements; identified and managed productive vector habitats.
5. Address travel and affordability together
Evidence: 250 respondents reported more than 5 km to care; 169 reported journeys exceeding 30 minutes.
Practical response: Plan outreach, referral transport and assistance for households unable to obtain essential prevention or care.
Measure next: Time to first assessment and completed referral; household out-of-pocket costs.
6. Measure what changes next
Evidence: The current sources provide a descriptive baseline, without a controlled follow-up.
Practical response: Track laboratory-confirmed cases, population denominators, seasonality, intervention coverage and clinical outcomes prospectively.
Measure next: Confirmed incidence with stable surveillance; severe cases and outcomes; coverage and missing-data trends.
Methods & transparent interpretation
What was measured, and what remains unknown
A locally led cross-sectional survey
Between March and July 2025, trained village cadres and Puskesmas staff collected household/environmental information and individual knowledge-and-experience responses using the offline-capable Kawan Against Malaria application. The reports describe 269 completed households from a target of 335 across 12 hamlets, and 460 individual interviews.
The 66 uncompleted planned locations included non-residential or out-of-area structures, unoccupied or renovated homes and dwellings lost to fire. The achieved sample should not be assumed representative of all Umalulu or East Sumba residents.
IMRaD report, Methods, p. 4
How this page calculates results
Counts come from the two aggregate analysis sheets in the supplied workbook. Percentages are recalculated as count ÷ displayed denominator × 100, rounded to one decimal. Missing answers remain explicit and are included in the module denominator, except the clearly labelled absence-duration subset (n=118).
No village-level breakdown, patient-level linkage, confidence interval, causal effect or combined risk score is inferred from these tables. The denominator for household-size responses is 256, so household totals must not be reconstructed as if all 269 had answered.
Reconciliation with the published 2025 summaries
- Nets: 182/269 households reported use by all sleeping groups (67.7%). The shorter reports describe this as sleeping-space coverage; the tables support a household-level result.
- Past malaria: 109/460 answered “ever”. Years include 2012–2018, so “within five years” is not supported for all 109.
- Transmission knowledge: 325 mentioned only Anopheles (70.7%); including mixed answers gives 355 (77.2%).
- Unscreened ventilation: the workbook records 122; the full narrative prints 121 beside 45.4%. This page uses 122/269 (45.4%).
- Water tanks: 17 affirmative entries, 237 without a tank and 15 unanswered. The 32 remaining households must not all be counted as owners.
- IRS: the workbook labels 66 responses “no answer”. These are not classified as verified absence of spraying.
- Questionnaire: some English v1.3 categories differ from the final workbook. The explorer uses the recorded table categories and does not invent a complete instrument-to-export mapping.
The downloadable originals are retained unchanged. These are transparent clarifications for this web edition, not silent revisions of the signed or controlled reports.
Clinical and statistical limitations
The study is descriptive and cross-sectional. Recall, selection, non-response, translation and questionnaire-routing issues may affect results. Reported malaria history was not systematically confirmed by contemporaneous parasitological testing. Test methods do not provide test positivity. The aggregate workbook does not allow deduplication, cross-tabulation or checks of individual response consistency.
Housing, standing water, livestock and sanitation observations do not establish causal effects on malaria. The documents’ August–November seasonality description should be treated as local contextual reporting until checked against dated, confirmed surveillance data. No prevented deaths, transmission reduction or treatment-success rate is estimated here.
Consent, contributions and funding
The IMRaD report states that local authorities coordinated the survey and verbal informed consent was obtained from adults, or guardians for minors. It reports removal of direct identifiers from the analysis dataset. The supplied aggregate workbook is not an individual patient dataset. No independent ethics-committee approval number is provided in the supplied reports.
Fair Future Foundation and Kawan Baik Indonesia worked with Umalulu village authorities, Melolo Puskesmas, the East Sumba District Health Office, PERDHAKI and the local enumerator team. Funding and support are credited to Australian Rotarians Against Malaria, the Rotary Club of Mandurah Districts, Rotary partners and Fair Future Foundation. The source reports declare no competing interests.
Read the full evidence
The reports, questionnaire and source tables
Six original documents accompany this web report. Read the scientific summary, inspect the detailed field narrative or check the counts in the supplied spreadsheet.
Financial transparency: original IDR statement
The original financial report records income and expenditure of IDR 135,717,860. Category amounts below sum to that expenditure total. This is the supplied statement; this page does not assert an independent financial audit.
| Expenditure category | IDR |
|---|---|
| Human resources | 10,000,000 |
| Field operations | 39,709,250 |
| Tools and materials, including nets and logistics | 53,107,000 |
| Data management | 26,230,000 |
| Education and socialisation | 6,360,131 |
| Administration | 311,479 |
The ARAM document also provides an AUD summary with different category allocations. It is linked separately; the two statements have not been treated as directly reconciled currency conversions.
Plain-language glossary
- RDT
- A rapid diagnostic test used to detect malaria parasite antigens.
- IRS
- Indoor residual spraying: applying an approved residual insecticide to appropriate indoor surfaces.
- LLIN / ITN
- An insecticide-treated mosquito net. Protection depends on access, use, condition and the suitability of the product.
- Cadre / kader
- A trained community health worker or volunteer; here, village malaria cadres help bring testing to homes.
- Puskesmas / Pustu
- A government primary-care centre / its auxiliary health post.
- Denominator
- The number of households or respondents used to calculate a percentage.
Web edition 1.0 · 20 September 2026 · Based on the supplied 2025 reports and aggregate workbook. Descriptive reanalysis and source reconciliation are stated above.
Contact Fair Future about this study · Explore the Sumba Sepsis Study 2026
