{
  "citation": "Nailul Huda dan Bhima Yudhistira Adhinegara. (2026). Yang Sesak Napas dan Yang Membayar Kerugian Ekonomi Kebakaran Hutan: Valuasi Kerugian Ekonomi Kebakaran Hutan Indonesia Januari sd Agustus 2026. CELIOS.",
  "publisher_url": "https://celios.co.id/the-hidden-cost-of-fire-economic-and-health-impacts-of-forest-and-land-fires-in-indonesia-2026/",
  "published": "2 September 2026 (laman penerbit)",
  "period": "Januari–Agustus 2026",
  "sha256": "ec7b792987373a592ddf611630454ede60924f29e596433230de7622f263c50a",
  "scope": "Pembacaan populer atas satu laporan estimasi, bukan pembaruan kondisi karhutla pada Oktober 2026. Cakupan kesehatan memuat 12 wilayah; Jawa Timur hanya empat kabupaten sekitar Bromo–Tengger–Semeru. Tabel ekonomi memuat 34 unit provinsi dan tidak sepenuhnya sama dengan daftar wilayah kebakaran.",
  "limits": "Jumlah penderita adalah hasil skenario prevalensi dan pengali, bukan registrasi pasien atau estimasi kausal kasus tambahan akibat asap. Rincian model ekonomi dan data mentah biaya belum cukup untuk mereplikasi seluruh hasil atau memastikan setiap komponen bebas tumpang tindih.",
  "regions": [
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      "name": "Kalimantan Barat",
      "area_ha": 38310.86,
      "population": 5750000,
      "diagnosis_prevalence": 1.1,
      "broad_prevalence": 15.4,
      "diagnosis_cases": 112585,
      "broad_cases": 1576150,
      "diagnosis_direct": 0.45,
      "diagnosis_indirect": 0.15,
      "diagnosis_total": 0.6,
      "broad_direct": 6.31,
      "broad_indirect": 2.15,
      "broad_total": 8.45
    },
    {
      "name": "Papua Selatan",
      "area_ha": 25838.53,
      "population": 562220,
      "diagnosis_prevalence": 3.6,
      "broad_prevalence": 27.7,
      "diagnosis_cases": 36027,
      "broad_cases": 277208,
      "diagnosis_direct": 0.14,
      "diagnosis_indirect": 0.07,
      "diagnosis_total": 0.22,
      "broad_direct": 1.11,
      "broad_indirect": 0.56,
      "broad_total": 1.67
    },
    {
      "name": "Nusa Tenggara Timur",
      "area_ha": 19565.16,
      "population": 5600000,
      "diagnosis_prevalence": 1,
      "broad_prevalence": 18.7,
      "diagnosis_cases": 99680,
      "broad_cases": 1864016,
      "diagnosis_direct": 0.4,
      "diagnosis_indirect": 0.11,
      "diagnosis_total": 0.51,
      "broad_direct": 7.46,
      "broad_indirect": 2.04,
      "broad_total": 9.5
    },
    {
      "name": "Nusa Tenggara Barat",
      "area_ha": 17406.46,
      "population": 5666314,
      "diagnosis_prevalence": 3.1,
      "broad_prevalence": 36.3,
      "diagnosis_cases": 312667,
      "broad_cases": 3661232,
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      "broad_indirect": 4.36,
      "broad_total": 19.01
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    {
      "name": "Riau",
      "area_ha": 15738.92,
      "population": 7490000,
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      "broad_prevalence": 13.6,
      "diagnosis_cases": 106658,
      "broad_cases": 1813179,
      "diagnosis_direct": 0.43,
      "diagnosis_indirect": 0.18,
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      "broad_indirect": 3.06,
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    {
      "name": "Maluku",
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      "population": 1870000,
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      "broad_prevalence": 14.3,
      "diagnosis_cases": 33286,
      "broad_cases": 475990,
      "diagnosis_direct": 0.13,
      "diagnosis_indirect": 0.05,
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      "broad_direct": 1.9,
      "broad_indirect": 0.71,
      "broad_total": 2.61
    },
    {
      "name": "Jawa Timur*",
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      "population": 6632162,
      "diagnosis_prevalence": 3.2,
      "broad_prevalence": 22.7,
      "diagnosis_cases": 377768,
      "broad_cases": 2679791,
      "diagnosis_direct": 1.51,
      "diagnosis_indirect": 0.41,
      "diagnosis_total": 1.92,
      "broad_direct": 10.72,
      "broad_indirect": 2.92,
      "broad_total": 13.65
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    {
      "name": "Kalimantan Selatan",
      "area_ha": 8019.63,
      "population": 4150000,
      "diagnosis_prevalence": 1.1,
      "broad_prevalence": 19.5,
      "diagnosis_cases": 81257,
      "broad_cases": 1440465,
      "diagnosis_direct": 0.33,
      "diagnosis_indirect": 0.13,
      "diagnosis_total": 0.46,
      "broad_direct": 5.76,
      "broad_indirect": 2.39,
      "broad_total": 8.16
    },
    {
      "name": "Kalimantan Tengah",
      "area_ha": 7634.46,
      "population": 2700000,
      "diagnosis_prevalence": 0.7,
      "broad_prevalence": 16.7,
      "diagnosis_cases": 33642,
      "broad_cases": 802602,
      "diagnosis_direct": 0.13,
      "diagnosis_indirect": 0.06,
      "diagnosis_total": 0.19,
      "broad_direct": 3.21,
      "broad_indirect": 1.32,
      "broad_total": 4.53
    },
    {
      "name": "Kepulauan Riau",
      "area_ha": 5760.9,
      "population": 2140000,
      "diagnosis_prevalence": 1,
      "broad_prevalence": 11.4,
      "diagnosis_cases": 38092,
      "broad_cases": 434249,
      "diagnosis_direct": 0.15,
      "diagnosis_indirect": 0.07,
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      "broad_direct": 1.74,
      "broad_indirect": 0.75,
      "broad_total": 2.49
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    {
      "name": "Sulawesi Tengah",
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      "broad_prevalence": 23.4,
      "diagnosis_cases": 49662,
      "broad_cases": 1291212,
      "diagnosis_direct": 0.2,
      "diagnosis_indirect": 0.07,
      "diagnosis_total": 0.27,
      "broad_direct": 5.17,
      "broad_indirect": 1.83,
      "broad_total": 7
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      "population": 1492290,
      "diagnosis_prevalence": 18.8,
      "broad_prevalence": 39.4,
      "diagnosis_cases": 499380,
      "broad_cases": 1046573,
      "diagnosis_direct": 2,
      "diagnosis_indirect": 0.95,
      "diagnosis_total": 2.95,
      "broad_direct": 4.19,
      "broad_indirect": 2,
      "broad_total": 6.19
    }
  ],
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      "name": "Aceh",
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      "loss_pct": 0.0183
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      "baseline_million": 202726215.4,
      "loss_pct": 0.3979
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    {
      "name": "DKI Jakarta",
      "loss_million": 1005602.73,
      "baseline_million": 2150040705.76,
      "loss_pct": 0.0468
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      "loss_million": 316093.26,
      "baseline_million": 1869555173.2,
      "loss_pct": 0.0169
    },
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      "name": "Jawa Tengah",
      "loss_million": 445974.22,
      "baseline_million": 1048914781.97,
      "loss_pct": 0.0425
    },
    {
      "name": "DI Yogyakarta",
      "loss_million": 29935.67,
      "baseline_million": 120302495.06,
      "loss_pct": 0.0249
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      "name": "Jawa Timur",
      "loss_million": 2344189.3,
      "baseline_million": 1884107401.35,
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      "baseline_million": 603234778.01,
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      "loss_million": 31407.83,
      "baseline_million": 192826509.59,
      "loss_pct": 0.0163
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      "loss_million": 2635321.13,
      "baseline_million": 121305889.08,
      "loss_pct": 2.1725
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      "baseline_million": 86629826.33,
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      "name": "Sulawesi Tenggara",
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      "baseline_million": 87518082.17,
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      "name": "Gorontalo",
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      "name": "Sulawesi Barat",
      "loss_million": 4205.21,
      "baseline_million": 32596657.85,
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      "name": "Maluku",
      "loss_million": 2245865.79,
      "baseline_million": 44340821.48,
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      "name": "Maluku Utara",
      "loss_million": 35661.6,
      "baseline_million": 32831893.33,
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    {
      "name": "Papua Barat",
      "loss_million": 4367900.51,
      "baseline_million": 67862465.15,
      "loss_pct": 6.4364
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    {
      "name": "Papua",
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      "baseline_million": 146364079.46,
      "loss_pct": 0.0165
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  ],
  "channels": [
    {
      "id": "keluarga",
      "name": "Keluarga",
      "steps": [
        "Paparan asap dan gangguan aktivitas",
        "Kebutuhan berobat atau merawat anggota keluarga",
        "Waktu kerja berkurang dan pengeluaran bertambah"
      ],
      "question": "Siapa membayar obat, perjalanan, dan hari kerja yang hilang?",
      "limit": "Skema ini menjelaskan jalur yang mungkin terjadi. Laporan tidak memisahkan persentase biaya yang benar-benar dibayar setiap rumah tangga."
    },
    {
      "id": "usaha",
      "name": "Usaha dan pekerja",
      "steps": [
        "Lahan atau kegiatan ekonomi terganggu",
        "Produksi, distribusi, atau penjualan tersendat",
        "Pendapatan usaha dan upah dapat tertekan"
      ],
      "question": "Seberapa mudah usaha bertahan, mengganti pasokan, atau memulihkan aset?",
      "limit": "Tidak semua kerugian adalah bangunan terbakar. Besar gangguan berbeda menurut sektor dan hubungan pasokannya."
    },
    {
      "id": "pemerintah",
      "name": "Layanan publik",
      "steps": [
        "Warga dan kegiatan usaha terdampak",
        "Kebutuhan layanan bertambah, aktivitas kena pajak melemah",
        "Ruang anggaran menghadapi tekanan"
      ],
      "question": "Apakah sumber daya layanan cukup ketika kebutuhan datang bersamaan?",
      "limit": "Biaya sosial, klaim BPJS, dan belanja APBN merupakan ukuran yang berbeda. PDF tidak menyediakan pembagian pembayar yang lengkap."
    }
  ],
  "issues": [
    [
      "Satuan pajak DKI Jakarta",
      "Narasi menyebut Rp67 triliun. Tabel 3 memuat 67.426,78 juta rupiah, setara sekitar Rp67,43 miliar. Artikel mengikuti satuan tabel.",
      "PDF hlm. 6 / tercetak 5"
    ],
    [
      "Urutan biaya kesehatan",
      "Narasi menempatkan Jawa Timur tertinggi pada skenario diagnosis, tetapi Tabel 5 menempatkan Papua Tengah di atasnya. Pada skenario luas, NTB berada di atas Jawa Timur menurut Tabel 7. Grafik mengikuti tabel.",
      "PDF hlm. 8–11 / tercetak 7–10"
    ],
    [
      "Prevalensi dan pengali 1,78",
      "Kolom prevalensi 2026 pada Tabel 4 mengulang angka dasar, sementara jumlah orang konsisten dengan pengali sekitar 1,78. Alat belajar menampilkan pengali itu secara terbuka.",
      "PDF hlm. 7–8 / tercetak 6–7"
    ],
    [
      "Perbedaan angka kecil dan cakupan",
      "Kalimantan Barat tercatat 1.576.150 orang pada Tabel 6, tetapi 1.576.190 pada Tabel 7. Grafik jumlah orang mengikuti Tabel 6. Total komponen diagnosis 7,13 + 2,63 = 9,76, sedangkan total laporan 9,75 triliun; kemungkinan pembulatan tidak dapat dikonfirmasi dari data mentah.",
      "PDF hlm. 9–11 / tercetak 8–10"
    ],
    [
      "Potensi tumpang tindih biaya",
      "Acuan Kiely dkk. mencakup komponen kesehatan serta emisi karbon. PDF tidak membuka rekonsiliasi lengkap yang memastikan tidak ada komponen bertumpang tindih dengan biaya kesehatan tambahan. Total ditampilkan sebagai klaim estimasi CELIOS.",
      "PDF hlm. 3–4 / tercetak 2–3; Kiely dkk. (2021)"
    ]
  ],
  "totals": {
    "economic_trillion": 29.54,
    "diagnosis_health_trillion": 9.75,
    "broad_health_trillion": 93.56,
    "diagnosis_direct": 7.13,
    "diagnosis_indirect": 2.63,
    "broad_direct": 69.48,
    "broad_indirect": 24.08,
    "diagnosis_cases": 1780704,
    "broad_cases": 17362707,
    "tax_loss_billion": 269.86087,
    "central_health_function_trillion": 138.426,
    "uplift_pct": 78
  },
  "secondary_sources": [
    {
      "name": "Kiely dkk. (2021), Nature Communications",
      "url": "https://doi.org/10.1038/s41467-021-27353-x",
      "use": "Memeriksa cakupan valuasi kerugian pada salah satu acuan laporan: kerusakan lahan, nilai emisi karbon, dan kesehatan jangka panjang. Cakupannya berbeda dari tagihan berobat."
    }
  ],
  "method_notes": [
    "Nilai wilayah disalin dari tabel PDF, bukan data mentah yang diverifikasi ulang pada portal kementerian.",
    "Grafik ekonomi menggunakan besar penurunan positif untuk memudahkan perbandingan; tanda sumber adalah negatif.",
    "Persentase area memakai jumlah 12 batang, bukan total resmi nasional.",
    "Simulasi keluarga rekaan; tidak memakai tarif BPJS atau memprediksi tagihan nyata.",
    "Kalkulator prevalensi hanya merekonstruksi perkalian sederhana; tidak mengekstrapolasi biaya kesehatan atau dampak ekonomi.",
    "Perbandingan anggaran memakai outlook 2026 dalam Tabel 8; bukan klaim anggaran aktual, realisasi, atau seluruh anggaran kesehatan nasional."
  ]
}